Overview

Dataset statistics

Number of variables276
Number of observations1000
Missing cells161096
Missing cells (%)58.4%
Total size in memory12.4 MiB
Average record size in memory12.7 KiB

Variable types

Numeric1
Text275

Alerts

section has constant value ""Constant
q23_r7_c1 has constant value ""Constant
q23_r7_c2 has constant value ""Constant
q23_r7_c3 has constant value ""Constant
q23_r7_c4 has constant value ""Constant
q1_1 has 51 (5.1%) missing valuesMissing
q1_2 has 51 (5.1%) missing valuesMissing
q1_3 has 51 (5.1%) missing valuesMissing
q16_c1_r1 has 452 (45.2%) missing valuesMissing
q16_c1_r2 has 452 (45.2%) missing valuesMissing
q16_c1_r3 has 452 (45.2%) missing valuesMissing
q16_c1_r4 has 452 (45.2%) missing valuesMissing
q16_c2_r1 has 455 (45.5%) missing valuesMissing
q16_c2_r2 has 455 (45.5%) missing valuesMissing
q16_c2_r3 has 455 (45.5%) missing valuesMissing
q16_c2_r4 has 455 (45.5%) missing valuesMissing
q16_c3_r1 has 467 (46.7%) missing valuesMissing
q16_c3_r2 has 467 (46.7%) missing valuesMissing
q16_c3_r3 has 467 (46.7%) missing valuesMissing
q16_c3_r4 has 467 (46.7%) missing valuesMissing
q16_c4_r1 has 507 (50.7%) missing valuesMissing
q16_c4_r2 has 507 (50.7%) missing valuesMissing
q16_c4_r3 has 507 (50.7%) missing valuesMissing
q16_c4_r4 has 507 (50.7%) missing valuesMissing
q16_c5_r1 has 552 (55.2%) missing valuesMissing
q16_c5_r2 has 552 (55.2%) missing valuesMissing
q16_c5_r3 has 552 (55.2%) missing valuesMissing
q16_c5_r4 has 552 (55.2%) missing valuesMissing
q16_c6_r1 has 617 (61.7%) missing valuesMissing
q16_c6_r2 has 617 (61.7%) missing valuesMissing
q16_c6_r3 has 617 (61.7%) missing valuesMissing
q16_c6_r4 has 617 (61.7%) missing valuesMissing
q16_c7_r1 has 673 (67.3%) missing valuesMissing
q16_c7_r2 has 673 (67.3%) missing valuesMissing
q16_c7_r3 has 673 (67.3%) missing valuesMissing
q16_c7_r4 has 673 (67.3%) missing valuesMissing
q16_c8_r1 has 730 (73.0%) missing valuesMissing
q16_c8_r2 has 730 (73.0%) missing valuesMissing
q16_c8_r3 has 730 (73.0%) missing valuesMissing
q16_c8_r4 has 730 (73.0%) missing valuesMissing
q16_c9_r1 has 796 (79.6%) missing valuesMissing
q16_c9_r2 has 796 (79.6%) missing valuesMissing
q16_c9_r3 has 796 (79.6%) missing valuesMissing
q16_c9_r4 has 796 (79.6%) missing valuesMissing
q16_c10_r1 has 842 (84.2%) missing valuesMissing
q16_c10_r2 has 842 (84.2%) missing valuesMissing
q16_c10_r3 has 842 (84.2%) missing valuesMissing
q16_c10_r4 has 842 (84.2%) missing valuesMissing
q16_c11_r1 has 887 (88.7%) missing valuesMissing
q16_c11_r2 has 887 (88.7%) missing valuesMissing
q16_c11_r3 has 887 (88.7%) missing valuesMissing
q16_c11_r4 has 887 (88.7%) missing valuesMissing
q16_c12_r1 has 912 (91.2%) missing valuesMissing
q16_c12_r2 has 912 (91.2%) missing valuesMissing
q16_c12_r3 has 912 (91.2%) missing valuesMissing
q16_c12_r4 has 912 (91.2%) missing valuesMissing
q16_c13_r1 has 934 (93.4%) missing valuesMissing
q16_c13_r2 has 934 (93.4%) missing valuesMissing
q16_c13_r3 has 934 (93.4%) missing valuesMissing
q16_c13_r4 has 934 (93.4%) missing valuesMissing
q16_c14_r1 has 947 (94.7%) missing valuesMissing
q16_c14_r2 has 947 (94.7%) missing valuesMissing
q16_c14_r3 has 947 (94.7%) missing valuesMissing
q16_c14_r4 has 947 (94.7%) missing valuesMissing
q16_c15_r1 has 960 (96.0%) missing valuesMissing
q16_c15_r2 has 960 (96.0%) missing valuesMissing
q16_c15_r3 has 960 (96.0%) missing valuesMissing
q16_c15_r4 has 960 (96.0%) missing valuesMissing
q16_c16_r1 has 969 (96.9%) missing valuesMissing
q16_c16_r2 has 969 (96.9%) missing valuesMissing
q16_c16_r3 has 969 (96.9%) missing valuesMissing
q16_c16_r4 has 969 (96.9%) missing valuesMissing
q16_c17_r1 has 973 (97.3%) missing valuesMissing
q16_c17_r2 has 973 (97.3%) missing valuesMissing
q16_c17_r3 has 973 (97.3%) missing valuesMissing
q16_c17_r4 has 973 (97.3%) missing valuesMissing
q16_c18_r1 has 977 (97.7%) missing valuesMissing
q16_c18_r2 has 977 (97.7%) missing valuesMissing
q16_c18_r3 has 977 (97.7%) missing valuesMissing
q16_c18_r4 has 977 (97.7%) missing valuesMissing
q16_c19_r1 has 978 (97.8%) missing valuesMissing
q16_c19_r2 has 978 (97.8%) missing valuesMissing
q16_c19_r3 has 978 (97.8%) missing valuesMissing
q16_c19_r4 has 978 (97.8%) missing valuesMissing
q16_c20_r1 has 980 (98.0%) missing valuesMissing
q16_c20_r2 has 980 (98.0%) missing valuesMissing
q16_c20_r3 has 980 (98.0%) missing valuesMissing
q16_c20_r4 has 980 (98.0%) missing valuesMissing
q16_c21_r1 has 983 (98.3%) missing valuesMissing
q16_c21_r2 has 983 (98.3%) missing valuesMissing
q16_c21_r3 has 983 (98.3%) missing valuesMissing
q16_c21_r4 has 983 (98.3%) missing valuesMissing
q16_c22_r1 has 986 (98.6%) missing valuesMissing
q16_c22_r2 has 986 (98.6%) missing valuesMissing
q16_c22_r3 has 986 (98.6%) missing valuesMissing
q16_c22_r4 has 986 (98.6%) missing valuesMissing
q16_c23_r1 has 989 (98.9%) missing valuesMissing
q16_c23_r2 has 989 (98.9%) missing valuesMissing
q16_c23_r3 has 989 (98.9%) missing valuesMissing
q16_c23_r4 has 989 (98.9%) missing valuesMissing
q17_c1_r1 has 452 (45.2%) missing valuesMissing
q17_c1_r2 has 452 (45.2%) missing valuesMissing
q17_c1_r3 has 452 (45.2%) missing valuesMissing
q17_c1_r4 has 452 (45.2%) missing valuesMissing
q17_c2_r1 has 455 (45.5%) missing valuesMissing
q17_c2_r2 has 455 (45.5%) missing valuesMissing
q17_c2_r3 has 455 (45.5%) missing valuesMissing
q17_c2_r4 has 455 (45.5%) missing valuesMissing
q17_c3_r1 has 465 (46.5%) missing valuesMissing
q17_c3_r2 has 465 (46.5%) missing valuesMissing
q17_c3_r3 has 465 (46.5%) missing valuesMissing
q17_c3_r4 has 465 (46.5%) missing valuesMissing
q17_c4_r1 has 500 (50.0%) missing valuesMissing
q17_c4_r2 has 500 (50.0%) missing valuesMissing
q17_c4_r3 has 500 (50.0%) missing valuesMissing
q17_c4_r4 has 500 (50.0%) missing valuesMissing
q17_c5_r1 has 551 (55.1%) missing valuesMissing
q17_c5_r2 has 551 (55.1%) missing valuesMissing
q17_c5_r3 has 551 (55.1%) missing valuesMissing
q17_c5_r4 has 551 (55.1%) missing valuesMissing
q17_c6_r1 has 617 (61.7%) missing valuesMissing
q17_c6_r2 has 617 (61.7%) missing valuesMissing
q17_c6_r3 has 617 (61.7%) missing valuesMissing
q17_c6_r4 has 617 (61.7%) missing valuesMissing
q17_c7_r1 has 679 (67.9%) missing valuesMissing
q17_c7_r2 has 679 (67.9%) missing valuesMissing
q17_c7_r3 has 679 (67.9%) missing valuesMissing
q17_c7_r4 has 679 (67.9%) missing valuesMissing
q17_c8_r1 has 734 (73.4%) missing valuesMissing
q17_c8_r2 has 734 (73.4%) missing valuesMissing
q17_c8_r3 has 734 (73.4%) missing valuesMissing
q17_c8_r4 has 734 (73.4%) missing valuesMissing
q17_c9_r1 has 808 (80.8%) missing valuesMissing
q17_c9_r2 has 808 (80.8%) missing valuesMissing
q17_c9_r3 has 808 (80.8%) missing valuesMissing
q17_c9_r4 has 808 (80.8%) missing valuesMissing
q17_c10_r1 has 854 (85.4%) missing valuesMissing
q17_c10_r2 has 854 (85.4%) missing valuesMissing
q17_c10_r3 has 854 (85.4%) missing valuesMissing
q17_c10_r4 has 854 (85.4%) missing valuesMissing
q17_c11_r1 has 898 (89.8%) missing valuesMissing
q17_c11_r2 has 898 (89.8%) missing valuesMissing
q17_c11_r3 has 898 (89.8%) missing valuesMissing
q17_c11_r4 has 898 (89.8%) missing valuesMissing
q17_c12_r1 has 921 (92.1%) missing valuesMissing
q17_c12_r2 has 921 (92.1%) missing valuesMissing
q17_c12_r3 has 921 (92.1%) missing valuesMissing
q17_c12_r4 has 921 (92.1%) missing valuesMissing
q17_c13_r1 has 938 (93.8%) missing valuesMissing
q17_c13_r2 has 938 (93.8%) missing valuesMissing
q17_c13_r3 has 938 (93.8%) missing valuesMissing
q17_c13_r4 has 938 (93.8%) missing valuesMissing
q17_c14_r1 has 951 (95.1%) missing valuesMissing
q17_c14_r2 has 951 (95.1%) missing valuesMissing
q17_c14_r3 has 951 (95.1%) missing valuesMissing
q17_c14_r4 has 951 (95.1%) missing valuesMissing
q17_c15_r1 has 959 (95.9%) missing valuesMissing
q17_c15_r2 has 959 (95.9%) missing valuesMissing
q17_c15_r3 has 959 (95.9%) missing valuesMissing
q17_c15_r4 has 959 (95.9%) missing valuesMissing
q17_c16_r1 has 970 (97.0%) missing valuesMissing
q17_c16_r2 has 970 (97.0%) missing valuesMissing
q17_c16_r3 has 970 (97.0%) missing valuesMissing
q17_c16_r4 has 970 (97.0%) missing valuesMissing
q26_1 has 111 (11.1%) missing valuesMissing
q26_2 has 139 (13.9%) missing valuesMissing
q26_3 has 75 (7.5%) missing valuesMissing
q26_4 has 125 (12.5%) missing valuesMissing
q26_5 has 27 (2.7%) missing valuesMissing
q27_1 has 815 (81.5%) missing valuesMissing
q27_2 has 974 (97.4%) missing valuesMissing
q27_3 has 566 (56.6%) missing valuesMissing
q27_4 has 827 (82.7%) missing valuesMissing
q27_5 has 369 (36.9%) missing valuesMissing
q40_r1_c1_1 has 293 (29.3%) missing valuesMissing
q40_r1_c2_1 has 936 (93.6%) missing valuesMissing
q40_r1_c3_1 has 303 (30.3%) missing valuesMissing
q40_r1_c4_1 has 312 (31.2%) missing valuesMissing
q40_r1_c5_1 has 308 (30.8%) missing valuesMissing
q40_r1_c6_1 has 330 (33.0%) missing valuesMissing
q40_r1_c7_1 has 344 (34.4%) missing valuesMissing
q40_r1_c8_1 has 312 (31.2%) missing valuesMissing
q40_r1_c9 has 956 (95.6%) missing valuesMissing
q40_r1_c10_1 has 968 (96.8%) missing valuesMissing
q40_r1_c1_2 has 618 (61.8%) missing valuesMissing
q40_r1_c2_2 has 967 (96.7%) missing valuesMissing
q40_r1_c3_2 has 621 (62.1%) missing valuesMissing
q40_r1_c4_2 has 624 (62.4%) missing valuesMissing
q40_r1_c5_2 has 627 (62.7%) missing valuesMissing
q40_r1_c6_2 has 635 (63.5%) missing valuesMissing
q40_r1_c7_2 has 639 (63.9%) missing valuesMissing
q40_r1_c8_2 has 628 (62.8%) missing valuesMissing
q40_r1_c10_2 has 992 (99.2%) missing valuesMissing
q40_r1_c1_3 has 751 (75.1%) missing valuesMissing
q40_r1_c2_3 has 981 (98.1%) missing valuesMissing
q40_r1_c3_3 has 753 (75.3%) missing valuesMissing
q40_r1_c4_3 has 756 (75.6%) missing valuesMissing
q40_r1_c5_3 has 755 (75.5%) missing valuesMissing
q40_r1_c6_3 has 759 (75.9%) missing valuesMissing
q40_r1_c7_3 has 761 (76.1%) missing valuesMissing
q40_r1_c8_3 has 758 (75.8%) missing valuesMissing
q40_r1_c10_3 has 994 (99.4%) missing valuesMissing
q40_r1_c1_4 has 828 (82.8%) missing valuesMissing
q40_r1_c2_4 has 969 (96.9%) missing valuesMissing
q40_r1_c3_4 has 831 (83.1%) missing valuesMissing
q40_r1_c4_4 has 832 (83.2%) missing valuesMissing
q40_r1_c5_4 has 832 (83.2%) missing valuesMissing
q40_r1_c6_4 has 837 (83.7%) missing valuesMissing
q40_r1_c7_4 has 836 (83.6%) missing valuesMissing
q40_r1_c8_4 has 836 (83.6%) missing valuesMissing
q40_r1_c10_4 has 993 (99.3%) missing valuesMissing
q40_r1_c1_5 has 892 (89.2%) missing valuesMissing
q40_r1_c2_5 has 978 (97.8%) missing valuesMissing
q40_r1_c3_5 has 893 (89.3%) missing valuesMissing
q40_r1_c4_5 has 894 (89.4%) missing valuesMissing
q40_r1_c5_5 has 892 (89.2%) missing valuesMissing
q40_r1_c6_5 has 895 (89.5%) missing valuesMissing
q40_r1_c7_5 has 895 (89.5%) missing valuesMissing
q40_r1_c8_5 has 896 (89.6%) missing valuesMissing
q40_r1_c10_5 has 993 (99.3%) missing valuesMissing
q42_1_rev has 87 (8.7%) missing valuesMissing
q43_1 has 823 (82.3%) missing valuesMissing
q44_2 has 18 (1.8%) missing valuesMissing
0 has unique valuesUnique
voterid has unique valuesUnique
q0_dbn has unique valuesUnique

Reproduction

Analysis started2023-12-09 22:14:21.977633
Analysis finished2023-12-09 22:14:31.531482
Duration9.55 seconds
Software versionydata-profiling v0.0.dev0
Download configurationconfig.json

Variables

0
Real number (ℝ)

UNIQUE 

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean500.5
Minimum1
Maximum1000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2023-12-09T22:14:32.067417image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile50.95
Q1250.75
median500.5
Q3750.25
95-th percentile950.05
Maximum1000
Range999
Interquartile range (IQR)499.5

Descriptive statistics

Standard deviation288.8194361
Coefficient of variation (CV)0.5770618104
Kurtosis-1.2
Mean500.5
Median Absolute Deviation (MAD)250
Skewness0
Sum500500
Variance83416.66667
MonotonicityStrictly increasing
2023-12-09T22:14:32.231651image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
672 1
 
0.1%
659 1
 
0.1%
660 1
 
0.1%
661 1
 
0.1%
662 1
 
0.1%
663 1
 
0.1%
664 1
 
0.1%
665 1
 
0.1%
666 1
 
0.1%
Other values (990) 990
99.0%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
ValueCountFrequency (%)
1000 1
0.1%
999 1
0.1%
998 1
0.1%
997 1
0.1%
996 1
0.1%

voterid
Text

UNIQUE 

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size60.3 KiB
2023-12-09T22:14:33.112812image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length5
Median length5
Mean length4.658
Min length4

Characters and Unicode

Total characters4658
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1000 ?
Unique (%)100.0%

Sample

1st row16862
2nd row1645
3rd row13175
4th row3706
5th row13812
ValueCountFrequency (%)
14783 1
 
0.1%
17964 1
 
0.1%
20266 1
 
0.1%
14946 1
 
0.1%
11438 1
 
0.1%
20405 1
 
0.1%
16482 1
 
0.1%
15770 1
 
0.1%
3741 1
 
0.1%
14975 1
 
0.1%
Other values (990) 990
99.0%
2023-12-09T22:14:33.777309image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 915
19.6%
2 594
12.8%
9 445
9.6%
8 417
9.0%
0 401
8.6%
6 398
8.5%
4 396
8.5%
7 387
8.3%
5 353
 
7.6%
3 352
 
7.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4658
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 915
19.6%
2 594
12.8%
9 445
9.6%
8 417
9.0%
0 401
8.6%
6 398
8.5%
4 396
8.5%
7 387
8.3%
5 353
 
7.6%
3 352
 
7.6%

Most occurring scripts

ValueCountFrequency (%)
Common 4658
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 915
19.6%
2 594
12.8%
9 445
9.6%
8 417
9.0%
0 401
8.6%
6 398
8.5%
4 396
8.5%
7 387
8.3%
5 353
 
7.6%
3 352
 
7.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4658
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 915
19.6%
2 594
12.8%
9 445
9.6%
8 417
9.0%
0 401
8.6%
6 398
8.5%
4 396
8.5%
7 387
8.3%
5 353
 
7.6%
3 352
 
7.6%

section
Text

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size56.8 KiB
2023-12-09T22:14:33.897044image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 1000
100.0%
2023-12-09T22:14:34.115047image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1000
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1000
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1000
100.0%

q0_dbn
Text

UNIQUE 

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size61.6 KiB
2023-12-09T22:14:34.533199image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters6000
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1000 ?
Unique (%)100.0%

Sample

1st row01M015
2nd row01M019
3rd row01M020
4th row01M034
5th row01M063
ValueCountFrequency (%)
24q455 1
 
0.1%
06m103 1
 
0.1%
08x367 1
 
0.1%
10x307 1
 
0.1%
05m133 1
 
0.1%
02m933 1
 
0.1%
13k350 1
 
0.1%
02m198 1
 
0.1%
22k109 1
 
0.1%
27q316 1
 
0.1%
Other values (990) 990
99.0%
2023-12-09T22:14:35.075927image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 891
14.8%
1 851
14.2%
0 843
14.1%
5 406
6.8%
4 396
6.6%
3 391
6.5%
K 323
 
5.4%
9 317
 
5.3%
6 315
 
5.2%
7 299
 
5.0%
Other values (4) 968
16.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5000
83.3%
Uppercase Letter 1000
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 891
17.8%
1 851
17.0%
0 843
16.9%
5 406
8.1%
4 396
7.9%
3 391
7.8%
9 317
 
6.3%
6 315
 
6.3%
7 299
 
6.0%
8 291
 
5.8%
Uppercase Letter
ValueCountFrequency (%)
K 323
32.3%
Q 240
24.0%
X 237
23.7%
M 200
20.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5000
83.3%
Latin 1000
 
16.7%

Most frequent character per script

Common
ValueCountFrequency (%)
2 891
17.8%
1 851
17.0%
0 843
16.9%
5 406
8.1%
4 396
7.9%
3 391
7.8%
9 317
 
6.3%
6 315
 
6.3%
7 299
 
6.0%
8 291
 
5.8%
Latin
ValueCountFrequency (%)
K 323
32.3%
Q 240
24.0%
X 237
23.7%
M 200
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 891
14.8%
1 851
14.2%
0 843
14.1%
5 406
6.8%
4 396
6.6%
3 391
6.5%
K 323
 
5.4%
9 317
 
5.3%
6 315
 
5.2%
7 299
 
5.0%
Other values (4) 968
16.1%

q1_1
Text

MISSING 

Distinct586
Distinct (%)61.7%
Missing51
Missing (%)5.1%
Memory size60.2 KiB
2023-12-09T22:14:35.396348image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length19
Median length11
Mean length6.13487882
Min length2

Characters and Unicode

Total characters5822
Distinct characters54
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique425 ?
Unique (%)44.8%

Sample

1st rowJacqueline
2nd rowRonnie
3rd rowBryan
4th rowJodi
5th rowAron
ValueCountFrequency (%)
jennifer 14
 
1.5%
michael 12
 
1.2%
lisa 9
 
0.9%
michelle 9
 
0.9%
karen 9
 
0.9%
elizabeth 8
 
0.8%
rachel 7
 
0.7%
christine 7
 
0.7%
mary 7
 
0.7%
nicole 7
 
0.7%
Other values (577) 872
90.7%
2023-12-09T22:14:35.848902image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 801
13.8%
e 663
 
11.4%
i 522
 
9.0%
n 505
 
8.7%
r 415
 
7.1%
l 311
 
5.3%
o 221
 
3.8%
t 207
 
3.6%
h 199
 
3.4%
s 197
 
3.4%
Other values (44) 1781
30.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4832
83.0%
Uppercase Letter 972
 
16.7%
Space Separator 12
 
0.2%
Dash Punctuation 4
 
0.1%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 801
16.6%
e 663
13.7%
i 522
10.8%
n 505
10.5%
r 415
8.6%
l 311
 
6.4%
o 221
 
4.6%
t 207
 
4.3%
h 199
 
4.1%
s 197
 
4.1%
Other values (16) 791
16.4%
Uppercase Letter
ValueCountFrequency (%)
J 112
11.5%
M 98
 
10.1%
A 81
 
8.3%
S 74
 
7.6%
C 73
 
7.5%
D 72
 
7.4%
K 63
 
6.5%
L 54
 
5.6%
R 48
 
4.9%
T 45
 
4.6%
Other values (15) 252
25.9%
Space Separator
ValueCountFrequency (%)
12
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 5804
99.7%
Common 18
 
0.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 801
13.8%
e 663
 
11.4%
i 522
 
9.0%
n 505
 
8.7%
r 415
 
7.2%
l 311
 
5.4%
o 221
 
3.8%
t 207
 
3.6%
h 199
 
3.4%
s 197
 
3.4%
Other values (41) 1763
30.4%
Common
ValueCountFrequency (%)
12
66.7%
- 4
 
22.2%
. 2
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5822
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 801
13.8%
e 663
 
11.4%
i 522
 
9.0%
n 505
 
8.7%
r 415
 
7.1%
l 311
 
5.3%
o 221
 
3.8%
t 207
 
3.6%
h 199
 
3.4%
s 197
 
3.4%
Other values (44) 1781
30.6%

q1_2
Text

MISSING 

Distinct868
Distinct (%)91.5%
Missing51
Missing (%)5.1%
Memory size61.0 KiB
2023-12-09T22:14:36.273350image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length19
Median length14
Mean length6.965226554
Min length2

Characters and Unicode

Total characters6610
Distinct characters54
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique818 ?
Unique (%)86.2%

Sample

1st rowDugan
2nd rowFilippatos
3rd rowGlover
4th rowFriedman
5th rowMichlin
ValueCountFrequency (%)
miller 5
 
0.5%
williams 5
 
0.5%
jones 4
 
0.4%
brown 4
 
0.4%
lee 4
 
0.4%
davis 4
 
0.4%
lopez 4
 
0.4%
cole 3
 
0.3%
thomas 3
 
0.3%
de 3
 
0.3%
Other values (872) 936
96.0%
2023-12-09T22:14:36.835443image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 673
 
10.2%
e 597
 
9.0%
o 514
 
7.8%
n 501
 
7.6%
r 483
 
7.3%
i 467
 
7.1%
l 395
 
6.0%
s 310
 
4.7%
t 214
 
3.2%
u 177
 
2.7%
Other values (44) 2279
34.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 5521
83.5%
Uppercase Letter 1030
 
15.6%
Dash Punctuation 30
 
0.5%
Space Separator 26
 
0.4%
Other Punctuation 3
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 673
12.2%
e 597
10.8%
o 514
9.3%
n 501
9.1%
r 483
8.7%
i 467
 
8.5%
l 395
 
7.2%
s 310
 
5.6%
t 214
 
3.9%
u 177
 
3.2%
Other values (16) 1190
21.6%
Uppercase Letter
ValueCountFrequency (%)
M 111
 
10.8%
S 102
 
9.9%
C 75
 
7.3%
R 70
 
6.8%
B 69
 
6.7%
D 60
 
5.8%
L 59
 
5.7%
G 59
 
5.7%
P 59
 
5.7%
A 48
 
4.7%
Other values (14) 318
30.9%
Other Punctuation
ValueCountFrequency (%)
' 2
66.7%
. 1
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 30
100.0%
Space Separator
ValueCountFrequency (%)
26
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 6551
99.1%
Common 59
 
0.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 673
 
10.3%
e 597
 
9.1%
o 514
 
7.8%
n 501
 
7.6%
r 483
 
7.4%
i 467
 
7.1%
l 395
 
6.0%
s 310
 
4.7%
t 214
 
3.3%
u 177
 
2.7%
Other values (40) 2220
33.9%
Common
ValueCountFrequency (%)
- 30
50.8%
26
44.1%
' 2
 
3.4%
. 1
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6610
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 673
 
10.2%
e 597
 
9.0%
o 514
 
7.8%
n 501
 
7.6%
r 483
 
7.3%
i 467
 
7.1%
l 395
 
6.0%
s 310
 
4.7%
t 214
 
3.2%
u 177
 
2.7%
Other values (44) 2279
34.5%

q1_3
Text

MISSING 

Distinct948
Distinct (%)99.9%
Missing51
Missing (%)5.1%
Memory size76.7 KiB
2023-12-09T22:14:37.156417image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length35
Median length32
Mean length23.86512118
Min length15

Characters and Unicode

Total characters22648
Distinct characters64
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique947 ?
Unique (%)99.8%

Sample

1st rowjdugan6@SCHOOLS.NYC.GOV
2nd rowrfilippatos@schools.nyc.gov
3rd rowbglover@schools.nyc.gov
4th rowjfriedman3@schools.nyc.gov
5th rowAMICHLIN@SCHOOLS.NYC.GOV
ValueCountFrequency (%)
jball3@schools.nyc.gov 2
 
0.2%
kpiazza2@schools.nyc.gov 1
 
0.1%
gdehaugoubart@schools.nyc.gov 1
 
0.1%
mgarfie@schools.nyc.gov 1
 
0.1%
mkelly2@schools.nyc.gov 1
 
0.1%
hcasado@schools.nyc.gov 1
 
0.1%
tbateshowell@schools.nyc.gov 1
 
0.1%
jnariman@schools.nyc.gov 1
 
0.1%
rbagg@schools.nyc.gov 1
 
0.1%
cwillia25@schools.nyc.gov 1
 
0.1%
Other values (938) 938
98.8%
2023-12-09T22:14:37.635218image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 2576
 
11.4%
. 1884
 
8.3%
s 1784
 
7.9%
c 1641
 
7.2%
n 1125
 
5.0%
l 1079
 
4.8%
@ 949
 
4.2%
h 857
 
3.8%
g 849
 
3.7%
y 795
 
3.5%
Other values (54) 9109
40.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 14779
65.3%
Uppercase Letter 4579
 
20.2%
Other Punctuation 2833
 
12.5%
Decimal Number 456
 
2.0%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 2576
17.4%
s 1784
12.1%
c 1641
11.1%
n 1125
7.6%
l 1079
 
7.3%
h 857
 
5.8%
g 849
 
5.7%
y 795
 
5.4%
v 775
 
5.2%
a 600
 
4.1%
Other values (16) 2698
18.3%
Uppercase Letter
ValueCountFrequency (%)
O 738
16.1%
S 546
11.9%
C 531
11.6%
L 340
 
7.4%
N 312
 
6.8%
G 276
 
6.0%
H 253
 
5.5%
V 243
 
5.3%
Y 239
 
5.2%
A 164
 
3.6%
Other values (15) 937
20.5%
Decimal Number
ValueCountFrequency (%)
2 180
39.5%
3 79
17.3%
1 41
 
9.0%
4 35
 
7.7%
6 31
 
6.8%
5 31
 
6.8%
7 24
 
5.3%
8 14
 
3.1%
9 13
 
2.9%
0 8
 
1.8%
Other Punctuation
ValueCountFrequency (%)
. 1884
66.5%
@ 949
33.5%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 19358
85.5%
Common 3290
 
14.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 2576
 
13.3%
s 1784
 
9.2%
c 1641
 
8.5%
n 1125
 
5.8%
l 1079
 
5.6%
h 857
 
4.4%
g 849
 
4.4%
y 795
 
4.1%
v 775
 
4.0%
O 738
 
3.8%
Other values (41) 7139
36.9%
Common
ValueCountFrequency (%)
. 1884
57.3%
@ 949
28.8%
2 180
 
5.5%
3 79
 
2.4%
1 41
 
1.2%
4 35
 
1.1%
6 31
 
0.9%
5 31
 
0.9%
7 24
 
0.7%
8 14
 
0.4%
Other values (3) 22
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 22648
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 2576
 
11.4%
. 1884
 
8.3%
s 1784
 
7.9%
c 1641
 
7.2%
n 1125
 
5.0%
l 1079
 
4.8%
@ 949
 
4.2%
h 857
 
3.8%
g 849
 
3.7%
y 795
 
3.5%
Other values (54) 9109
40.2%

q16_c1_r1
Text

MISSING 

Distinct36
Distinct (%)6.6%
Missing452
Missing (%)45.2%
Memory size45.4 KiB
2023-12-09T22:14:37.813240image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.173357664
Min length1

Characters and Unicode

Total characters643
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)2.4%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 398
72.6%
10 23
 
4.2%
1 19
 
3.5%
20 14
 
2.6%
5 8
 
1.5%
25 8
 
1.5%
2 8
 
1.5%
8 7
 
1.3%
6 7
 
1.3%
12 6
 
1.1%
Other values (26) 50
 
9.1%
2023-12-09T22:14:38.125663image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 451
70.1%
1 73
 
11.4%
2 40
 
6.2%
5 23
 
3.6%
3 15
 
2.3%
8 11
 
1.7%
6 11
 
1.7%
4 10
 
1.6%
7 7
 
1.1%
9 2
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 643
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 451
70.1%
1 73
 
11.4%
2 40
 
6.2%
5 23
 
3.6%
3 15
 
2.3%
8 11
 
1.7%
6 11
 
1.7%
4 10
 
1.6%
7 7
 
1.1%
9 2
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
Common 643
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 451
70.1%
1 73
 
11.4%
2 40
 
6.2%
5 23
 
3.6%
3 15
 
2.3%
8 11
 
1.7%
6 11
 
1.7%
4 10
 
1.6%
7 7
 
1.1%
9 2
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 643
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 451
70.1%
1 73
 
11.4%
2 40
 
6.2%
5 23
 
3.6%
3 15
 
2.3%
8 11
 
1.7%
6 11
 
1.7%
4 10
 
1.6%
7 7
 
1.1%
9 2
 
0.3%

q16_c1_r2
Text

MISSING 

Distinct44
Distinct (%)8.0%
Missing452
Missing (%)45.2%
Memory size45.4 KiB
2023-12-09T22:14:38.314453image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length4
Median length1
Mean length1.224452555
Min length1

Characters and Unicode

Total characters671
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)2.7%

Sample

1st row30
2nd row0
3rd row35
4th row0
5th row0
ValueCountFrequency (%)
0 373
68.1%
1 23
 
4.2%
5 18
 
3.3%
20 16
 
2.9%
10 13
 
2.4%
30 8
 
1.5%
12 8
 
1.5%
2 7
 
1.3%
50 7
 
1.3%
40 6
 
1.1%
Other values (34) 69
 
12.6%
2023-12-09T22:14:38.624302image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 440
65.6%
1 68
 
10.1%
2 50
 
7.5%
5 44
 
6.6%
3 26
 
3.9%
4 18
 
2.7%
6 10
 
1.5%
8 7
 
1.0%
7 6
 
0.9%
9 2
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 671
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 440
65.6%
1 68
 
10.1%
2 50
 
7.5%
5 44
 
6.6%
3 26
 
3.9%
4 18
 
2.7%
6 10
 
1.5%
8 7
 
1.0%
7 6
 
0.9%
9 2
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
Common 671
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 440
65.6%
1 68
 
10.1%
2 50
 
7.5%
5 44
 
6.6%
3 26
 
3.9%
4 18
 
2.7%
6 10
 
1.5%
8 7
 
1.0%
7 6
 
0.9%
9 2
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 671
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 440
65.6%
1 68
 
10.1%
2 50
 
7.5%
5 44
 
6.6%
3 26
 
3.9%
4 18
 
2.7%
6 10
 
1.5%
8 7
 
1.0%
7 6
 
0.9%
9 2
 
0.3%

q16_c1_r3
Text

MISSING 

Distinct31
Distinct (%)5.7%
Missing452
Missing (%)45.2%
Memory size45.4 KiB
2023-12-09T22:14:38.787244image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.125912409
Min length1

Characters and Unicode

Total characters617
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)2.2%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 434
79.2%
10 19
 
3.5%
5 17
 
3.1%
1 10
 
1.8%
20 9
 
1.6%
2 9
 
1.6%
12 5
 
0.9%
30 5
 
0.9%
25 4
 
0.7%
3 4
 
0.7%
Other values (21) 32
 
5.8%
2023-12-09T22:14:39.088510image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 477
77.3%
1 47
 
7.6%
2 29
 
4.7%
5 27
 
4.4%
3 13
 
2.1%
8 7
 
1.1%
6 6
 
1.0%
4 5
 
0.8%
7 3
 
0.5%
9 3
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 617
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 477
77.3%
1 47
 
7.6%
2 29
 
4.7%
5 27
 
4.4%
3 13
 
2.1%
8 7
 
1.1%
6 6
 
1.0%
4 5
 
0.8%
7 3
 
0.5%
9 3
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
Common 617
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 477
77.3%
1 47
 
7.6%
2 29
 
4.7%
5 27
 
4.4%
3 13
 
2.1%
8 7
 
1.1%
6 6
 
1.0%
4 5
 
0.8%
7 3
 
0.5%
9 3
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 617
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 477
77.3%
1 47
 
7.6%
2 29
 
4.7%
5 27
 
4.4%
3 13
 
2.1%
8 7
 
1.1%
6 6
 
1.0%
4 5
 
0.8%
7 3
 
0.5%
9 3
 
0.5%

q16_c1_r4
Text

MISSING 

Distinct45
Distinct (%)8.2%
Missing452
Missing (%)45.2%
Memory size45.4 KiB
2023-12-09T22:14:39.277261image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.226277372
Min length1

Characters and Unicode

Total characters672
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)3.3%

Sample

1st row0
2nd row30
3rd row35
4th row0
5th row0
ValueCountFrequency (%)
0 375
68.4%
20 16
 
2.9%
10 15
 
2.7%
1 13
 
2.4%
40 11
 
2.0%
5 10
 
1.8%
2 9
 
1.6%
30 9
 
1.6%
3 8
 
1.5%
25 7
 
1.3%
Other values (35) 75
 
13.7%
2023-12-09T22:14:39.605025image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 446
66.4%
1 59
 
8.8%
2 43
 
6.4%
5 35
 
5.2%
3 29
 
4.3%
4 24
 
3.6%
8 16
 
2.4%
6 11
 
1.6%
9 5
 
0.7%
7 4
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 672
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 446
66.4%
1 59
 
8.8%
2 43
 
6.4%
5 35
 
5.2%
3 29
 
4.3%
4 24
 
3.6%
8 16
 
2.4%
6 11
 
1.6%
9 5
 
0.7%
7 4
 
0.6%

Most occurring scripts

ValueCountFrequency (%)
Common 672
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 446
66.4%
1 59
 
8.8%
2 43
 
6.4%
5 35
 
5.2%
3 29
 
4.3%
4 24
 
3.6%
8 16
 
2.4%
6 11
 
1.6%
9 5
 
0.7%
7 4
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 672
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 446
66.4%
1 59
 
8.8%
2 43
 
6.4%
5 35
 
5.2%
3 29
 
4.3%
4 24
 
3.6%
8 16
 
2.4%
6 11
 
1.6%
9 5
 
0.7%
7 4
 
0.6%

q16_c2_r1
Text

MISSING 

Distinct36
Distinct (%)6.6%
Missing455
Missing (%)45.5%
Memory size45.3 KiB
2023-12-09T22:14:40.033576image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.177981651
Min length1

Characters and Unicode

Total characters642
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)2.6%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 392
71.9%
10 24
 
4.4%
1 20
 
3.7%
20 14
 
2.6%
2 10
 
1.8%
6 9
 
1.7%
25 8
 
1.5%
12 8
 
1.5%
5 8
 
1.5%
8 5
 
0.9%
Other values (26) 47
 
8.6%
2023-12-09T22:14:40.344074image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 447
69.6%
1 74
 
11.5%
2 44
 
6.9%
5 23
 
3.6%
6 13
 
2.0%
3 13
 
2.0%
4 11
 
1.7%
8 9
 
1.4%
7 6
 
0.9%
9 2
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 642
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 447
69.6%
1 74
 
11.5%
2 44
 
6.9%
5 23
 
3.6%
6 13
 
2.0%
3 13
 
2.0%
4 11
 
1.7%
8 9
 
1.4%
7 6
 
0.9%
9 2
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
Common 642
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 447
69.6%
1 74
 
11.5%
2 44
 
6.9%
5 23
 
3.6%
6 13
 
2.0%
3 13
 
2.0%
4 11
 
1.7%
8 9
 
1.4%
7 6
 
0.9%
9 2
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 642
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 447
69.6%
1 74
 
11.5%
2 44
 
6.9%
5 23
 
3.6%
6 13
 
2.0%
3 13
 
2.0%
4 11
 
1.7%
8 9
 
1.4%
7 6
 
0.9%
9 2
 
0.3%

q16_c2_r2
Text

MISSING 

Distinct46
Distinct (%)8.4%
Missing455
Missing (%)45.5%
Memory size45.3 KiB
2023-12-09T22:14:40.531769image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length4
Median length1
Mean length1.222018349
Min length1

Characters and Unicode

Total characters666
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)3.3%

Sample

1st row30
2nd row0
3rd row35
4th row0
5th row0
ValueCountFrequency (%)
0 371
68.1%
1 22
 
4.0%
5 18
 
3.3%
20 16
 
2.9%
10 11
 
2.0%
2 9
 
1.7%
50 7
 
1.3%
40 7
 
1.3%
30 7
 
1.3%
25 6
 
1.1%
Other values (36) 71
 
13.0%
2023-12-09T22:14:40.841411image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 435
65.3%
1 63
 
9.5%
2 51
 
7.7%
5 45
 
6.8%
3 25
 
3.8%
4 22
 
3.3%
6 11
 
1.7%
8 7
 
1.1%
7 5
 
0.8%
9 2
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 666
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 435
65.3%
1 63
 
9.5%
2 51
 
7.7%
5 45
 
6.8%
3 25
 
3.8%
4 22
 
3.3%
6 11
 
1.7%
8 7
 
1.1%
7 5
 
0.8%
9 2
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
Common 666
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 435
65.3%
1 63
 
9.5%
2 51
 
7.7%
5 45
 
6.8%
3 25
 
3.8%
4 22
 
3.3%
6 11
 
1.7%
8 7
 
1.1%
7 5
 
0.8%
9 2
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 666
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 435
65.3%
1 63
 
9.5%
2 51
 
7.7%
5 45
 
6.8%
3 25
 
3.8%
4 22
 
3.3%
6 11
 
1.7%
8 7
 
1.1%
7 5
 
0.8%
9 2
 
0.3%

q16_c2_r3
Text

MISSING 

Distinct30
Distinct (%)5.5%
Missing455
Missing (%)45.5%
Memory size45.3 KiB
2023-12-09T22:14:41.003543image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.124770642
Min length1

Characters and Unicode

Total characters613
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)1.8%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 432
79.3%
10 19
 
3.5%
5 17
 
3.1%
20 10
 
1.8%
1 10
 
1.8%
2 10
 
1.8%
30 5
 
0.9%
25 4
 
0.7%
12 4
 
0.7%
3 3
 
0.6%
Other values (20) 31
 
5.7%
2023-12-09T22:14:41.316788image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 476
77.7%
1 46
 
7.5%
2 29
 
4.7%
5 27
 
4.4%
3 12
 
2.0%
6 6
 
1.0%
8 6
 
1.0%
4 6
 
1.0%
9 3
 
0.5%
7 2
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 613
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 476
77.7%
1 46
 
7.5%
2 29
 
4.7%
5 27
 
4.4%
3 12
 
2.0%
6 6
 
1.0%
8 6
 
1.0%
4 6
 
1.0%
9 3
 
0.5%
7 2
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
Common 613
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 476
77.7%
1 46
 
7.5%
2 29
 
4.7%
5 27
 
4.4%
3 12
 
2.0%
6 6
 
1.0%
8 6
 
1.0%
4 6
 
1.0%
9 3
 
0.5%
7 2
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 613
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 476
77.7%
1 46
 
7.5%
2 29
 
4.7%
5 27
 
4.4%
3 12
 
2.0%
6 6
 
1.0%
8 6
 
1.0%
4 6
 
1.0%
9 3
 
0.5%
7 2
 
0.3%

q16_c2_r4
Text

MISSING 

Distinct44
Distinct (%)8.1%
Missing455
Missing (%)45.5%
Memory size45.3 KiB
2023-12-09T22:14:41.508230image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.231192661
Min length1

Characters and Unicode

Total characters671
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)3.3%

Sample

1st row0
2nd row30
3rd row35
4th row0
5th row0
ValueCountFrequency (%)
0 368
67.5%
10 15
 
2.8%
20 15
 
2.8%
1 14
 
2.6%
40 12
 
2.2%
5 10
 
1.8%
2 10
 
1.8%
3 8
 
1.5%
25 8
 
1.5%
30 8
 
1.5%
Other values (34) 77
 
14.1%
2023-12-09T22:14:41.831759image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 438
65.3%
1 61
 
9.1%
2 45
 
6.7%
5 37
 
5.5%
3 27
 
4.0%
4 26
 
3.9%
8 16
 
2.4%
6 12
 
1.8%
9 5
 
0.7%
7 4
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 671
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 438
65.3%
1 61
 
9.1%
2 45
 
6.7%
5 37
 
5.5%
3 27
 
4.0%
4 26
 
3.9%
8 16
 
2.4%
6 12
 
1.8%
9 5
 
0.7%
7 4
 
0.6%

Most occurring scripts

ValueCountFrequency (%)
Common 671
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 438
65.3%
1 61
 
9.1%
2 45
 
6.7%
5 37
 
5.5%
3 27
 
4.0%
4 26
 
3.9%
8 16
 
2.4%
6 12
 
1.8%
9 5
 
0.7%
7 4
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 671
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 438
65.3%
1 61
 
9.1%
2 45
 
6.7%
5 37
 
5.5%
3 27
 
4.0%
4 26
 
3.9%
8 16
 
2.4%
6 12
 
1.8%
9 5
 
0.7%
7 4
 
0.6%

q16_c3_r1
Text

MISSING 

Distinct34
Distinct (%)6.4%
Missing467
Missing (%)46.7%
Memory size45.0 KiB
2023-12-09T22:14:42.000094image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.181988743
Min length1

Characters and Unicode

Total characters630
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)2.3%

Sample

1st row0
2nd row0
3rd row0
4th row10
5th row0
ValueCountFrequency (%)
0 379
71.1%
10 25
 
4.7%
1 20
 
3.8%
20 14
 
2.6%
2 11
 
2.1%
12 9
 
1.7%
6 8
 
1.5%
25 8
 
1.5%
5 7
 
1.3%
8 7
 
1.3%
Other values (24) 45
 
8.4%
2023-12-09T22:14:42.300705image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 434
68.9%
1 76
 
12.1%
2 45
 
7.1%
5 22
 
3.5%
6 12
 
1.9%
3 12
 
1.9%
8 11
 
1.7%
4 11
 
1.7%
7 5
 
0.8%
9 2
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 630
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 434
68.9%
1 76
 
12.1%
2 45
 
7.1%
5 22
 
3.5%
6 12
 
1.9%
3 12
 
1.9%
8 11
 
1.7%
4 11
 
1.7%
7 5
 
0.8%
9 2
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
Common 630
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 434
68.9%
1 76
 
12.1%
2 45
 
7.1%
5 22
 
3.5%
6 12
 
1.9%
3 12
 
1.9%
8 11
 
1.7%
4 11
 
1.7%
7 5
 
0.8%
9 2
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 630
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 434
68.9%
1 76
 
12.1%
2 45
 
7.1%
5 22
 
3.5%
6 12
 
1.9%
3 12
 
1.9%
8 11
 
1.7%
4 11
 
1.7%
7 5
 
0.8%
9 2
 
0.3%

q16_c3_r2
Text

MISSING 

Distinct46
Distinct (%)8.6%
Missing467
Missing (%)46.7%
Memory size45.0 KiB
2023-12-09T22:14:42.490511image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length4
Median length1
Mean length1.225140713
Min length1

Characters and Unicode

Total characters653
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)3.6%

Sample

1st row30
2nd row0
3rd row35
4th row0
5th row30
ValueCountFrequency (%)
0 359
67.4%
1 23
 
4.3%
5 18
 
3.4%
20 16
 
3.0%
10 13
 
2.4%
2 9
 
1.7%
12 8
 
1.5%
30 7
 
1.3%
50 7
 
1.3%
25 6
 
1.1%
Other values (36) 67
 
12.6%
2023-12-09T22:14:42.808146image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 422
64.6%
1 67
 
10.3%
2 52
 
8.0%
5 45
 
6.9%
3 21
 
3.2%
4 19
 
2.9%
6 12
 
1.8%
8 7
 
1.1%
7 5
 
0.8%
9 3
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 653
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 422
64.6%
1 67
 
10.3%
2 52
 
8.0%
5 45
 
6.9%
3 21
 
3.2%
4 19
 
2.9%
6 12
 
1.8%
8 7
 
1.1%
7 5
 
0.8%
9 3
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
Common 653
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 422
64.6%
1 67
 
10.3%
2 52
 
8.0%
5 45
 
6.9%
3 21
 
3.2%
4 19
 
2.9%
6 12
 
1.8%
8 7
 
1.1%
7 5
 
0.8%
9 3
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 653
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 422
64.6%
1 67
 
10.3%
2 52
 
8.0%
5 45
 
6.9%
3 21
 
3.2%
4 19
 
2.9%
6 12
 
1.8%
8 7
 
1.1%
7 5
 
0.8%
9 3
 
0.5%

q16_c3_r3
Text

MISSING 

Distinct31
Distinct (%)5.8%
Missing467
Missing (%)46.7%
Memory size45.0 KiB
2023-12-09T22:14:42.973228image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.131332083
Min length1

Characters and Unicode

Total characters603
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)2.4%

Sample

1st row0
2nd row0
3rd row0
4th row10
5th row0
ValueCountFrequency (%)
0 418
78.4%
10 19
 
3.6%
5 16
 
3.0%
1 11
 
2.1%
2 11
 
2.1%
20 9
 
1.7%
12 6
 
1.1%
30 5
 
0.9%
25 4
 
0.8%
3 3
 
0.6%
Other values (21) 31
 
5.8%
2023-12-09T22:14:43.269094image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 461
76.5%
1 51
 
8.5%
2 31
 
5.1%
5 26
 
4.3%
3 12
 
2.0%
8 7
 
1.2%
6 6
 
1.0%
4 5
 
0.8%
7 2
 
0.3%
9 2
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 603
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 461
76.5%
1 51
 
8.5%
2 31
 
5.1%
5 26
 
4.3%
3 12
 
2.0%
8 7
 
1.2%
6 6
 
1.0%
4 5
 
0.8%
7 2
 
0.3%
9 2
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
Common 603
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 461
76.5%
1 51
 
8.5%
2 31
 
5.1%
5 26
 
4.3%
3 12
 
2.0%
8 7
 
1.2%
6 6
 
1.0%
4 5
 
0.8%
7 2
 
0.3%
9 2
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 603
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 461
76.5%
1 51
 
8.5%
2 31
 
5.1%
5 26
 
4.3%
3 12
 
2.0%
8 7
 
1.2%
6 6
 
1.0%
4 5
 
0.8%
7 2
 
0.3%
9 2
 
0.3%

q16_c3_r4
Text

MISSING 

Distinct43
Distinct (%)8.1%
Missing467
Missing (%)46.7%
Memory size45.0 KiB
2023-12-09T22:14:43.450905image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.22326454
Min length1

Characters and Unicode

Total characters652
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)3.2%

Sample

1st row0
2nd row30
3rd row35
4th row0
5th row15
ValueCountFrequency (%)
0 366
68.7%
10 15
 
2.8%
20 13
 
2.4%
1 13
 
2.4%
40 10
 
1.9%
2 10
 
1.9%
5 9
 
1.7%
25 8
 
1.5%
30 8
 
1.5%
3 7
 
1.3%
Other values (33) 74
 
13.9%
2023-12-09T22:14:43.775042image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 431
66.1%
1 58
 
8.9%
2 41
 
6.3%
5 37
 
5.7%
3 27
 
4.1%
4 23
 
3.5%
8 16
 
2.5%
6 10
 
1.5%
9 5
 
0.8%
7 4
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 652
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 431
66.1%
1 58
 
8.9%
2 41
 
6.3%
5 37
 
5.7%
3 27
 
4.1%
4 23
 
3.5%
8 16
 
2.5%
6 10
 
1.5%
9 5
 
0.8%
7 4
 
0.6%

Most occurring scripts

ValueCountFrequency (%)
Common 652
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 431
66.1%
1 58
 
8.9%
2 41
 
6.3%
5 37
 
5.7%
3 27
 
4.1%
4 23
 
3.5%
8 16
 
2.5%
6 10
 
1.5%
9 5
 
0.8%
7 4
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 652
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 431
66.1%
1 58
 
8.9%
2 41
 
6.3%
5 37
 
5.7%
3 27
 
4.1%
4 23
 
3.5%
8 16
 
2.5%
6 10
 
1.5%
9 5
 
0.8%
7 4
 
0.6%

q16_c4_r1
Text

MISSING 

Distinct35
Distinct (%)7.1%
Missing507
Missing (%)50.7%
Memory size44.0 KiB
2023-12-09T22:14:43.944068image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.176470588
Min length1

Characters and Unicode

Total characters580
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)2.6%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 352
71.4%
10 20
 
4.1%
1 19
 
3.9%
20 14
 
2.8%
2 9
 
1.8%
6 8
 
1.6%
25 7
 
1.4%
5 7
 
1.4%
8 7
 
1.4%
30 5
 
1.0%
Other values (25) 45
 
9.1%
2023-12-09T22:14:44.261712image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 402
69.3%
1 66
 
11.4%
2 38
 
6.6%
5 20
 
3.4%
6 12
 
2.1%
3 12
 
2.1%
8 11
 
1.9%
4 11
 
1.9%
7 6
 
1.0%
9 2
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 580
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 402
69.3%
1 66
 
11.4%
2 38
 
6.6%
5 20
 
3.4%
6 12
 
2.1%
3 12
 
2.1%
8 11
 
1.9%
4 11
 
1.9%
7 6
 
1.0%
9 2
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
Common 580
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 402
69.3%
1 66
 
11.4%
2 38
 
6.6%
5 20
 
3.4%
6 12
 
2.1%
3 12
 
2.1%
8 11
 
1.9%
4 11
 
1.9%
7 6
 
1.0%
9 2
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 580
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 402
69.3%
1 66
 
11.4%
2 38
 
6.6%
5 20
 
3.4%
6 12
 
2.1%
3 12
 
2.1%
8 11
 
1.9%
4 11
 
1.9%
7 6
 
1.0%
9 2
 
0.3%

q16_c4_r2
Text

MISSING 

Distinct43
Distinct (%)8.7%
Missing507
Missing (%)50.7%
Memory size44.0 KiB
2023-12-09T22:14:44.443083image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.210953347
Min length1

Characters and Unicode

Total characters597
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)3.0%

Sample

1st row30
2nd row0
3rd row35
4th row30
5th row0
ValueCountFrequency (%)
0 336
68.2%
1 20
 
4.1%
5 16
 
3.2%
20 13
 
2.6%
10 12
 
2.4%
30 7
 
1.4%
2 7
 
1.4%
40 6
 
1.2%
50 6
 
1.2%
12 6
 
1.2%
Other values (33) 64
 
13.0%
2023-12-09T22:14:44.755448image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 389
65.2%
1 59
 
9.9%
2 41
 
6.9%
5 40
 
6.7%
3 22
 
3.7%
4 20
 
3.4%
6 9
 
1.5%
7 8
 
1.3%
8 7
 
1.2%
9 2
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 597
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 389
65.2%
1 59
 
9.9%
2 41
 
6.9%
5 40
 
6.7%
3 22
 
3.7%
4 20
 
3.4%
6 9
 
1.5%
7 8
 
1.3%
8 7
 
1.2%
9 2
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
Common 597
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 389
65.2%
1 59
 
9.9%
2 41
 
6.9%
5 40
 
6.7%
3 22
 
3.7%
4 20
 
3.4%
6 9
 
1.5%
7 8
 
1.3%
8 7
 
1.2%
9 2
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 597
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 389
65.2%
1 59
 
9.9%
2 41
 
6.9%
5 40
 
6.7%
3 22
 
3.7%
4 20
 
3.4%
6 9
 
1.5%
7 8
 
1.3%
8 7
 
1.2%
9 2
 
0.3%

q16_c4_r3
Text

MISSING 

Distinct29
Distinct (%)5.9%
Missing507
Missing (%)50.7%
Memory size43.9 KiB
2023-12-09T22:14:44.912467image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.115618661
Min length1

Characters and Unicode

Total characters550
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)2.4%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 392
79.5%
10 16
 
3.2%
5 15
 
3.0%
1 11
 
2.2%
2 9
 
1.8%
20 8
 
1.6%
30 5
 
1.0%
12 4
 
0.8%
6 3
 
0.6%
25 3
 
0.6%
Other values (19) 27
 
5.5%
2023-12-09T22:14:45.203824image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 427
77.6%
1 41
 
7.5%
5 25
 
4.5%
2 25
 
4.5%
3 12
 
2.2%
6 6
 
1.1%
8 6
 
1.1%
4 4
 
0.7%
7 2
 
0.4%
9 2
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 550
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 427
77.6%
1 41
 
7.5%
5 25
 
4.5%
2 25
 
4.5%
3 12
 
2.2%
6 6
 
1.1%
8 6
 
1.1%
4 4
 
0.7%
7 2
 
0.4%
9 2
 
0.4%

Most occurring scripts

ValueCountFrequency (%)
Common 550
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 427
77.6%
1 41
 
7.5%
5 25
 
4.5%
2 25
 
4.5%
3 12
 
2.2%
6 6
 
1.1%
8 6
 
1.1%
4 4
 
0.7%
7 2
 
0.4%
9 2
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 550
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 427
77.6%
1 41
 
7.5%
5 25
 
4.5%
2 25
 
4.5%
3 12
 
2.2%
6 6
 
1.1%
8 6
 
1.1%
4 4
 
0.7%
7 2
 
0.4%
9 2
 
0.4%

q16_c4_r4
Text

MISSING 

Distinct42
Distinct (%)8.5%
Missing507
Missing (%)50.7%
Memory size44.0 KiB
2023-12-09T22:14:45.392114image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.229208925
Min length1

Characters and Unicode

Total characters606
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)2.8%

Sample

1st row0
2nd row30
3rd row35
4th row15
5th row0
ValueCountFrequency (%)
0 332
67.3%
20 14
 
2.8%
10 14
 
2.8%
1 13
 
2.6%
40 11
 
2.2%
2 9
 
1.8%
3 8
 
1.6%
5 8
 
1.6%
25 7
 
1.4%
30 7
 
1.4%
Other values (32) 70
 
14.2%
2023-12-09T22:14:45.710898image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 396
65.3%
1 54
 
8.9%
2 39
 
6.4%
5 31
 
5.1%
3 26
 
4.3%
4 22
 
3.6%
8 15
 
2.5%
6 12
 
2.0%
7 6
 
1.0%
9 5
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 606
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 396
65.3%
1 54
 
8.9%
2 39
 
6.4%
5 31
 
5.1%
3 26
 
4.3%
4 22
 
3.6%
8 15
 
2.5%
6 12
 
2.0%
7 6
 
1.0%
9 5
 
0.8%

Most occurring scripts

ValueCountFrequency (%)
Common 606
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 396
65.3%
1 54
 
8.9%
2 39
 
6.4%
5 31
 
5.1%
3 26
 
4.3%
4 22
 
3.6%
8 15
 
2.5%
6 12
 
2.0%
7 6
 
1.0%
9 5
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 606
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 396
65.3%
1 54
 
8.9%
2 39
 
6.4%
5 31
 
5.1%
3 26
 
4.3%
4 22
 
3.6%
8 15
 
2.5%
6 12
 
2.0%
7 6
 
1.0%
9 5
 
0.8%

q16_c5_r1
Text

MISSING 

Distinct33
Distinct (%)7.4%
Missing552
Missing (%)55.2%
Memory size42.8 KiB
2023-12-09T22:14:45.875472image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.167410714
Min length1

Characters and Unicode

Total characters523
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)3.1%

Sample

1st row0
2nd row0
3rd row0
4th row180
5th row8
ValueCountFrequency (%)
0 330
73.7%
10 19
 
4.2%
1 15
 
3.3%
20 12
 
2.7%
2 9
 
2.0%
25 7
 
1.6%
5 6
 
1.3%
6 6
 
1.3%
30 5
 
1.1%
8 4
 
0.9%
Other values (23) 35
 
7.8%
2023-12-09T22:14:46.175770image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 374
71.5%
1 54
 
10.3%
2 34
 
6.5%
5 18
 
3.4%
6 10
 
1.9%
3 10
 
1.9%
4 9
 
1.7%
8 8
 
1.5%
7 4
 
0.8%
9 2
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 523
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 374
71.5%
1 54
 
10.3%
2 34
 
6.5%
5 18
 
3.4%
6 10
 
1.9%
3 10
 
1.9%
4 9
 
1.7%
8 8
 
1.5%
7 4
 
0.8%
9 2
 
0.4%

Most occurring scripts

ValueCountFrequency (%)
Common 523
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 374
71.5%
1 54
 
10.3%
2 34
 
6.5%
5 18
 
3.4%
6 10
 
1.9%
3 10
 
1.9%
4 9
 
1.7%
8 8
 
1.5%
7 4
 
0.8%
9 2
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 523
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 374
71.5%
1 54
 
10.3%
2 34
 
6.5%
5 18
 
3.4%
6 10
 
1.9%
3 10
 
1.9%
4 9
 
1.7%
8 8
 
1.5%
7 4
 
0.8%
9 2
 
0.4%

q16_c5_r2
Text

MISSING 

Distinct42
Distinct (%)9.4%
Missing552
Missing (%)55.2%
Memory size42.8 KiB
2023-12-09T22:14:46.353414image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.207589286
Min length1

Characters and Unicode

Total characters541
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)3.6%

Sample

1st row30
2nd row35
3rd row30
4th row180
5th row16
ValueCountFrequency (%)
0 309
69.0%
1 16
 
3.6%
5 13
 
2.9%
20 11
 
2.5%
10 11
 
2.5%
30 7
 
1.6%
2 7
 
1.6%
50 6
 
1.3%
40 6
 
1.3%
8 4
 
0.9%
Other values (32) 58
 
12.9%
2023-12-09T22:14:46.685477image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 355
65.6%
1 51
 
9.4%
2 37
 
6.8%
5 34
 
6.3%
3 21
 
3.9%
4 18
 
3.3%
6 9
 
1.7%
8 7
 
1.3%
7 6
 
1.1%
9 3
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 541
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 355
65.6%
1 51
 
9.4%
2 37
 
6.8%
5 34
 
6.3%
3 21
 
3.9%
4 18
 
3.3%
6 9
 
1.7%
8 7
 
1.3%
7 6
 
1.1%
9 3
 
0.6%

Most occurring scripts

ValueCountFrequency (%)
Common 541
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 355
65.6%
1 51
 
9.4%
2 37
 
6.8%
5 34
 
6.3%
3 21
 
3.9%
4 18
 
3.3%
6 9
 
1.7%
8 7
 
1.3%
7 6
 
1.1%
9 3
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 541
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 355
65.6%
1 51
 
9.4%
2 37
 
6.8%
5 34
 
6.3%
3 21
 
3.9%
4 18
 
3.3%
6 9
 
1.7%
8 7
 
1.3%
7 6
 
1.1%
9 3
 
0.6%

q16_c5_r3
Text

MISSING 

Distinct27
Distinct (%)6.0%
Missing552
Missing (%)55.2%
Memory size42.8 KiB
2023-12-09T22:14:46.840813image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.116071429
Min length1

Characters and Unicode

Total characters500
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)2.5%

Sample

1st row0
2nd row0
3rd row0
4th row180
5th row0
ValueCountFrequency (%)
0 356
79.5%
10 15
 
3.3%
2 12
 
2.7%
5 12
 
2.7%
1 8
 
1.8%
20 8
 
1.8%
30 5
 
1.1%
6 3
 
0.7%
25 3
 
0.7%
12 3
 
0.7%
Other values (17) 23
 
5.1%
2023-12-09T22:14:47.425104image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 388
77.6%
1 37
 
7.4%
2 27
 
5.4%
5 20
 
4.0%
3 9
 
1.8%
8 6
 
1.2%
6 5
 
1.0%
4 4
 
0.8%
7 2
 
0.4%
9 2
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 500
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 388
77.6%
1 37
 
7.4%
2 27
 
5.4%
5 20
 
4.0%
3 9
 
1.8%
8 6
 
1.2%
6 5
 
1.0%
4 4
 
0.8%
7 2
 
0.4%
9 2
 
0.4%

Most occurring scripts

ValueCountFrequency (%)
Common 500
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 388
77.6%
1 37
 
7.4%
2 27
 
5.4%
5 20
 
4.0%
3 9
 
1.8%
8 6
 
1.2%
6 5
 
1.0%
4 4
 
0.8%
7 2
 
0.4%
9 2
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 500
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 388
77.6%
1 37
 
7.4%
2 27
 
5.4%
5 20
 
4.0%
3 9
 
1.8%
8 6
 
1.2%
6 5
 
1.0%
4 4
 
0.8%
7 2
 
0.4%
9 2
 
0.4%

q16_c5_r4
Text

MISSING 

Distinct41
Distinct (%)9.2%
Missing552
Missing (%)55.2%
Memory size42.8 KiB
2023-12-09T22:14:47.602047image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.216517857
Min length1

Characters and Unicode

Total characters545
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)4.0%

Sample

1st row0
2nd row35
3rd row15
4th row110
5th row0
ValueCountFrequency (%)
0 310
69.2%
10 15
 
3.3%
20 12
 
2.7%
40 9
 
2.0%
2 9
 
2.0%
1 8
 
1.8%
5 7
 
1.6%
3 6
 
1.3%
30 6
 
1.3%
6 6
 
1.3%
Other values (31) 60
 
13.4%
2023-12-09T22:14:47.926580image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 364
66.8%
1 45
 
8.3%
2 36
 
6.6%
5 27
 
5.0%
3 23
 
4.2%
4 21
 
3.9%
6 11
 
2.0%
8 11
 
2.0%
9 4
 
0.7%
7 3
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 545
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 364
66.8%
1 45
 
8.3%
2 36
 
6.6%
5 27
 
5.0%
3 23
 
4.2%
4 21
 
3.9%
6 11
 
2.0%
8 11
 
2.0%
9 4
 
0.7%
7 3
 
0.6%

Most occurring scripts

ValueCountFrequency (%)
Common 545
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 364
66.8%
1 45
 
8.3%
2 36
 
6.6%
5 27
 
5.0%
3 23
 
4.2%
4 21
 
3.9%
6 11
 
2.0%
8 11
 
2.0%
9 4
 
0.7%
7 3
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 545
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 364
66.8%
1 45
 
8.3%
2 36
 
6.6%
5 27
 
5.0%
3 23
 
4.2%
4 21
 
3.9%
6 11
 
2.0%
8 11
 
2.0%
9 4
 
0.7%
7 3
 
0.6%

q16_c6_r1
Text

MISSING 

Distinct30
Distinct (%)7.8%
Missing617
Missing (%)61.7%
Memory size41.2 KiB
2023-12-09T22:14:48.091409image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.167101828
Min length1

Characters and Unicode

Total characters447
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)3.4%

Sample

1st row0
2nd row6
3rd row25
4th row0
5th row0
ValueCountFrequency (%)
0 284
74.2%
10 17
 
4.4%
1 13
 
3.4%
20 10
 
2.6%
2 6
 
1.6%
30 6
 
1.6%
6 6
 
1.6%
25 5
 
1.3%
12 4
 
1.0%
5 3
 
0.8%
Other values (20) 29
 
7.6%
2023-12-09T22:14:48.393712image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 320
71.6%
1 48
 
10.7%
2 28
 
6.3%
5 12
 
2.7%
3 11
 
2.5%
6 10
 
2.2%
4 8
 
1.8%
8 5
 
1.1%
7 3
 
0.7%
9 2
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 447
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 320
71.6%
1 48
 
10.7%
2 28
 
6.3%
5 12
 
2.7%
3 11
 
2.5%
6 10
 
2.2%
4 8
 
1.8%
8 5
 
1.1%
7 3
 
0.7%
9 2
 
0.4%

Most occurring scripts

ValueCountFrequency (%)
Common 447
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 320
71.6%
1 48
 
10.7%
2 28
 
6.3%
5 12
 
2.7%
3 11
 
2.5%
6 10
 
2.2%
4 8
 
1.8%
8 5
 
1.1%
7 3
 
0.7%
9 2
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 447
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 320
71.6%
1 48
 
10.7%
2 28
 
6.3%
5 12
 
2.7%
3 11
 
2.5%
6 10
 
2.2%
4 8
 
1.8%
8 5
 
1.1%
7 3
 
0.7%
9 2
 
0.4%

q16_c6_r2
Text

MISSING 

Distinct36
Distinct (%)9.4%
Missing617
Missing (%)61.7%
Memory size41.2 KiB
2023-12-09T22:14:48.561458image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.17232376
Min length1

Characters and Unicode

Total characters449
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)3.9%

Sample

1st row35
2nd row5
3rd row25
4th row0
5th row0
ValueCountFrequency (%)
0 280
73.1%
1 13
 
3.4%
10 11
 
2.9%
5 9
 
2.3%
20 9
 
2.3%
40 6
 
1.6%
2 5
 
1.3%
30 4
 
1.0%
8 4
 
1.0%
25 3
 
0.8%
Other values (26) 39
 
10.2%
2023-12-09T22:14:48.868977image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 316
70.4%
1 38
 
8.5%
2 26
 
5.8%
5 24
 
5.3%
4 16
 
3.6%
3 13
 
2.9%
6 5
 
1.1%
7 5
 
1.1%
8 4
 
0.9%
9 2
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 449
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 316
70.4%
1 38
 
8.5%
2 26
 
5.8%
5 24
 
5.3%
4 16
 
3.6%
3 13
 
2.9%
6 5
 
1.1%
7 5
 
1.1%
8 4
 
0.9%
9 2
 
0.4%

Most occurring scripts

ValueCountFrequency (%)
Common 449
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 316
70.4%
1 38
 
8.5%
2 26
 
5.8%
5 24
 
5.3%
4 16
 
3.6%
3 13
 
2.9%
6 5
 
1.1%
7 5
 
1.1%
8 4
 
0.9%
9 2
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 449
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 316
70.4%
1 38
 
8.5%
2 26
 
5.8%
5 24
 
5.3%
4 16
 
3.6%
3 13
 
2.9%
6 5
 
1.1%
7 5
 
1.1%
8 4
 
0.9%
9 2
 
0.4%

q16_c6_r3
Text

MISSING 

Distinct26
Distinct (%)6.8%
Missing617
Missing (%)61.7%
Memory size41.1 KiB
2023-12-09T22:14:49.025282image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.109660574
Min length1

Characters and Unicode

Total characters425
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)3.7%

Sample

1st row0
2nd row0
3rd row10
4th row0
5th row0
ValueCountFrequency (%)
0 308
80.4%
10 14
 
3.7%
1 9
 
2.3%
2 9
 
2.3%
5 8
 
2.1%
20 7
 
1.8%
30 4
 
1.0%
35 2
 
0.5%
6 2
 
0.5%
25 2
 
0.5%
Other values (16) 18
 
4.7%
2023-12-09T22:14:49.327188image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 334
78.6%
1 31
 
7.3%
2 21
 
4.9%
5 15
 
3.5%
3 10
 
2.4%
8 4
 
0.9%
6 4
 
0.9%
4 4
 
0.9%
9 1
 
0.2%
7 1
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 425
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 334
78.6%
1 31
 
7.3%
2 21
 
4.9%
5 15
 
3.5%
3 10
 
2.4%
8 4
 
0.9%
6 4
 
0.9%
4 4
 
0.9%
9 1
 
0.2%
7 1
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Common 425
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 334
78.6%
1 31
 
7.3%
2 21
 
4.9%
5 15
 
3.5%
3 10
 
2.4%
8 4
 
0.9%
6 4
 
0.9%
4 4
 
0.9%
9 1
 
0.2%
7 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 425
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 334
78.6%
1 31
 
7.3%
2 21
 
4.9%
5 15
 
3.5%
3 10
 
2.4%
8 4
 
0.9%
6 4
 
0.9%
4 4
 
0.9%
9 1
 
0.2%
7 1
 
0.2%

q16_c6_r4
Text

MISSING 

Distinct36
Distinct (%)9.4%
Missing617
Missing (%)61.7%
Memory size41.2 KiB
2023-12-09T22:14:49.498983image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.195822454
Min length1

Characters and Unicode

Total characters458
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)4.4%

Sample

1st row35
2nd row0
3rd row25
4th row0
5th row0
ValueCountFrequency (%)
0 272
71.0%
20 12
 
3.1%
10 12
 
3.1%
40 10
 
2.6%
1 10
 
2.6%
2 8
 
2.1%
3 6
 
1.6%
4 4
 
1.0%
6 4
 
1.0%
25 4
 
1.0%
Other values (26) 41
 
10.7%
2023-12-09T22:14:49.814461image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 318
69.4%
1 35
 
7.6%
2 29
 
6.3%
4 20
 
4.4%
3 17
 
3.7%
5 17
 
3.7%
6 9
 
2.0%
8 7
 
1.5%
9 4
 
0.9%
7 2
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 458
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 318
69.4%
1 35
 
7.6%
2 29
 
6.3%
4 20
 
4.4%
3 17
 
3.7%
5 17
 
3.7%
6 9
 
2.0%
8 7
 
1.5%
9 4
 
0.9%
7 2
 
0.4%

Most occurring scripts

ValueCountFrequency (%)
Common 458
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 318
69.4%
1 35
 
7.6%
2 29
 
6.3%
4 20
 
4.4%
3 17
 
3.7%
5 17
 
3.7%
6 9
 
2.0%
8 7
 
1.5%
9 4
 
0.9%
7 2
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 458
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 318
69.4%
1 35
 
7.6%
2 29
 
6.3%
4 20
 
4.4%
3 17
 
3.7%
5 17
 
3.7%
6 9
 
2.0%
8 7
 
1.5%
9 4
 
0.9%
7 2
 
0.4%

q16_c7_r1
Text

MISSING 

Distinct31
Distinct (%)9.5%
Missing673
Missing (%)67.3%
Memory size39.7 KiB
2023-12-09T22:14:49.985231image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.168195719
Min length1

Characters and Unicode

Total characters382
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)4.3%

Sample

1st row6
2nd row25
3rd row0
4th row3
5th row0
ValueCountFrequency (%)
0 238
72.8%
1 13
 
4.0%
10 11
 
3.4%
20 10
 
3.1%
6 6
 
1.8%
25 6
 
1.8%
12 4
 
1.2%
2 4
 
1.2%
30 4
 
1.2%
5 3
 
0.9%
Other values (21) 28
 
8.6%
2023-12-09T22:14:50.291271image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 267
69.9%
1 39
 
10.2%
2 27
 
7.1%
5 12
 
3.1%
3 11
 
2.9%
6 10
 
2.6%
4 8
 
2.1%
8 4
 
1.0%
9 2
 
0.5%
7 2
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 382
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 267
69.9%
1 39
 
10.2%
2 27
 
7.1%
5 12
 
3.1%
3 11
 
2.9%
6 10
 
2.6%
4 8
 
2.1%
8 4
 
1.0%
9 2
 
0.5%
7 2
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
Common 382
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 267
69.9%
1 39
 
10.2%
2 27
 
7.1%
5 12
 
3.1%
3 11
 
2.9%
6 10
 
2.6%
4 8
 
2.1%
8 4
 
1.0%
9 2
 
0.5%
7 2
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 382
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 267
69.9%
1 39
 
10.2%
2 27
 
7.1%
5 12
 
3.1%
3 11
 
2.9%
6 10
 
2.6%
4 8
 
2.1%
8 4
 
1.0%
9 2
 
0.5%
7 2
 
0.5%

q16_c7_r2
Text

MISSING 

Distinct34
Distinct (%)10.4%
Missing673
Missing (%)67.3%
Memory size39.7 KiB
2023-12-09T22:14:50.465131image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.165137615
Min length1

Characters and Unicode

Total characters381
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)4.6%

Sample

1st row5
2nd row25
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 240
73.4%
1 14
 
4.3%
10 8
 
2.4%
20 8
 
2.4%
5 6
 
1.8%
2 5
 
1.5%
40 4
 
1.2%
30 3
 
0.9%
15 3
 
0.9%
25 3
 
0.9%
Other values (24) 33
 
10.1%
2023-12-09T22:14:50.782925image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 268
70.3%
1 34
 
8.9%
2 23
 
6.0%
5 19
 
5.0%
4 13
 
3.4%
3 11
 
2.9%
6 5
 
1.3%
7 3
 
0.8%
9 3
 
0.8%
8 2
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 381
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 268
70.3%
1 34
 
8.9%
2 23
 
6.0%
5 19
 
5.0%
4 13
 
3.4%
3 11
 
2.9%
6 5
 
1.3%
7 3
 
0.8%
9 3
 
0.8%
8 2
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
Common 381
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 268
70.3%
1 34
 
8.9%
2 23
 
6.0%
5 19
 
5.0%
4 13
 
3.4%
3 11
 
2.9%
6 5
 
1.3%
7 3
 
0.8%
9 3
 
0.8%
8 2
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 381
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 268
70.3%
1 34
 
8.9%
2 23
 
6.0%
5 19
 
5.0%
4 13
 
3.4%
3 11
 
2.9%
6 5
 
1.3%
7 3
 
0.8%
9 3
 
0.8%
8 2
 
0.5%

q16_c7_r3
Text

MISSING 

Distinct19
Distinct (%)5.8%
Missing673
Missing (%)67.3%
Memory size39.7 KiB
2023-12-09T22:14:50.928848image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.110091743
Min length1

Characters and Unicode

Total characters363
Distinct characters9
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)2.1%

Sample

1st row0
2nd row10
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 264
80.7%
10 13
 
4.0%
2 9
 
2.8%
1 7
 
2.1%
20 7
 
2.1%
5 5
 
1.5%
30 4
 
1.2%
6 3
 
0.9%
18 2
 
0.6%
35 2
 
0.6%
Other values (9) 11
 
3.4%
2023-12-09T22:14:51.204686image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 288
79.3%
1 25
 
6.9%
2 19
 
5.2%
5 11
 
3.0%
3 8
 
2.2%
8 5
 
1.4%
6 4
 
1.1%
4 2
 
0.6%
9 1
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 363
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 288
79.3%
1 25
 
6.9%
2 19
 
5.2%
5 11
 
3.0%
3 8
 
2.2%
8 5
 
1.4%
6 4
 
1.1%
4 2
 
0.6%
9 1
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
Common 363
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 288
79.3%
1 25
 
6.9%
2 19
 
5.2%
5 11
 
3.0%
3 8
 
2.2%
8 5
 
1.4%
6 4
 
1.1%
4 2
 
0.6%
9 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 363
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 288
79.3%
1 25
 
6.9%
2 19
 
5.2%
5 11
 
3.0%
3 8
 
2.2%
8 5
 
1.4%
6 4
 
1.1%
4 2
 
0.6%
9 1
 
0.3%

q16_c7_r4
Text

MISSING 

Distinct32
Distinct (%)9.8%
Missing673
Missing (%)67.3%
Memory size39.7 KiB
2023-12-09T22:14:51.369597image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.177370031
Min length1

Characters and Unicode

Total characters385
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)4.0%

Sample

1st row0
2nd row25
3rd row0
4th row1
5th row0
ValueCountFrequency (%)
0 240
73.4%
20 9
 
2.8%
1 8
 
2.4%
40 8
 
2.4%
10 8
 
2.4%
2 5
 
1.5%
4 5
 
1.5%
25 4
 
1.2%
3 4
 
1.2%
5 4
 
1.2%
Other values (22) 32
 
9.8%
2023-12-09T22:14:51.679547image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 272
70.6%
1 28
 
7.3%
2 22
 
5.7%
4 17
 
4.4%
5 16
 
4.2%
3 13
 
3.4%
8 7
 
1.8%
6 6
 
1.6%
9 3
 
0.8%
7 1
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 385
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 272
70.6%
1 28
 
7.3%
2 22
 
5.7%
4 17
 
4.4%
5 16
 
4.2%
3 13
 
3.4%
8 7
 
1.8%
6 6
 
1.6%
9 3
 
0.8%
7 1
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
Common 385
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 272
70.6%
1 28
 
7.3%
2 22
 
5.7%
4 17
 
4.4%
5 16
 
4.2%
3 13
 
3.4%
8 7
 
1.8%
6 6
 
1.6%
9 3
 
0.8%
7 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 385
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 272
70.6%
1 28
 
7.3%
2 22
 
5.7%
4 17
 
4.4%
5 16
 
4.2%
3 13
 
3.4%
8 7
 
1.8%
6 6
 
1.6%
9 3
 
0.8%
7 1
 
0.3%

q16_c8_r1
Text

MISSING 

Distinct27
Distinct (%)10.0%
Missing730
Missing (%)73.0%
Memory size38.3 KiB
2023-12-09T22:14:51.836324image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.166666667
Min length1

Characters and Unicode

Total characters315
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)4.4%

Sample

1st row6
2nd row0
3rd row3
4th row0
5th row0
ValueCountFrequency (%)
0 200
74.1%
10 10
 
3.7%
1 9
 
3.3%
20 8
 
3.0%
25 5
 
1.9%
6 5
 
1.9%
30 4
 
1.5%
12 3
 
1.1%
3 2
 
0.7%
14 2
 
0.7%
Other values (17) 22
 
8.1%
2023-12-09T22:14:52.123918image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 224
71.1%
1 31
 
9.8%
2 21
 
6.7%
3 10
 
3.2%
5 8
 
2.5%
6 8
 
2.5%
4 7
 
2.2%
8 3
 
1.0%
9 2
 
0.6%
7 1
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 315
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 224
71.1%
1 31
 
9.8%
2 21
 
6.7%
3 10
 
3.2%
5 8
 
2.5%
6 8
 
2.5%
4 7
 
2.2%
8 3
 
1.0%
9 2
 
0.6%
7 1
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
Common 315
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 224
71.1%
1 31
 
9.8%
2 21
 
6.7%
3 10
 
3.2%
5 8
 
2.5%
6 8
 
2.5%
4 7
 
2.2%
8 3
 
1.0%
9 2
 
0.6%
7 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 315
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 224
71.1%
1 31
 
9.8%
2 21
 
6.7%
3 10
 
3.2%
5 8
 
2.5%
6 8
 
2.5%
4 7
 
2.2%
8 3
 
1.0%
9 2
 
0.6%
7 1
 
0.3%

q16_c8_r2
Text

MISSING 

Distinct32
Distinct (%)11.9%
Missing730
Missing (%)73.0%
Memory size38.3 KiB
2023-12-09T22:14:52.287364image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.162962963
Min length1

Characters and Unicode

Total characters314
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)5.6%

Sample

1st row5
2nd row0
3rd row0
4th row0
5th row32
ValueCountFrequency (%)
0 202
74.8%
1 9
 
3.3%
10 6
 
2.2%
5 6
 
2.2%
20 6
 
2.2%
40 4
 
1.5%
8 2
 
0.7%
3 2
 
0.7%
30 2
 
0.7%
25 2
 
0.7%
Other values (22) 29
 
10.7%
2023-12-09T22:14:52.591450image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 224
71.3%
1 25
 
8.0%
5 17
 
5.4%
2 17
 
5.4%
4 11
 
3.5%
3 9
 
2.9%
7 4
 
1.3%
8 3
 
1.0%
6 3
 
1.0%
9 1
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 314
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 224
71.3%
1 25
 
8.0%
5 17
 
5.4%
2 17
 
5.4%
4 11
 
3.5%
3 9
 
2.9%
7 4
 
1.3%
8 3
 
1.0%
6 3
 
1.0%
9 1
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
Common 314
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 224
71.3%
1 25
 
8.0%
5 17
 
5.4%
2 17
 
5.4%
4 11
 
3.5%
3 9
 
2.9%
7 4
 
1.3%
8 3
 
1.0%
6 3
 
1.0%
9 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 314
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 224
71.3%
1 25
 
8.0%
5 17
 
5.4%
2 17
 
5.4%
4 11
 
3.5%
3 9
 
2.9%
7 4
 
1.3%
8 3
 
1.0%
6 3
 
1.0%
9 1
 
0.3%

q16_c8_r3
Text

MISSING 

Distinct19
Distinct (%)7.0%
Missing730
Missing (%)73.0%
Memory size38.3 KiB
2023-12-09T22:14:52.733365image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.103703704
Min length1

Characters and Unicode

Total characters298
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)3.7%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 219
81.1%
10 9
 
3.3%
20 7
 
2.6%
5 6
 
2.2%
2 6
 
2.2%
1 5
 
1.9%
30 3
 
1.1%
8 3
 
1.1%
25 2
 
0.7%
9 1
 
0.4%
Other values (9) 9
 
3.3%
2023-12-09T22:14:52.992019image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 238
79.9%
1 18
 
6.0%
2 16
 
5.4%
5 11
 
3.7%
3 5
 
1.7%
8 4
 
1.3%
4 2
 
0.7%
6 2
 
0.7%
9 1
 
0.3%
7 1
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 298
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 238
79.9%
1 18
 
6.0%
2 16
 
5.4%
5 11
 
3.7%
3 5
 
1.7%
8 4
 
1.3%
4 2
 
0.7%
6 2
 
0.7%
9 1
 
0.3%
7 1
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
Common 298
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 238
79.9%
1 18
 
6.0%
2 16
 
5.4%
5 11
 
3.7%
3 5
 
1.7%
8 4
 
1.3%
4 2
 
0.7%
6 2
 
0.7%
9 1
 
0.3%
7 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 298
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 238
79.9%
1 18
 
6.0%
2 16
 
5.4%
5 11
 
3.7%
3 5
 
1.7%
8 4
 
1.3%
4 2
 
0.7%
6 2
 
0.7%
9 1
 
0.3%
7 1
 
0.3%

q16_c8_r4
Text

MISSING 

Distinct32
Distinct (%)11.9%
Missing730
Missing (%)73.0%
Memory size38.3 KiB
2023-12-09T22:14:53.162377image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.188888889
Min length1

Characters and Unicode

Total characters321
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)5.6%

Sample

1st row0
2nd row0
3rd row1
4th row0
5th row40
ValueCountFrequency (%)
0 197
73.0%
20 9
 
3.3%
10 8
 
3.0%
40 6
 
2.2%
5 5
 
1.9%
1 4
 
1.5%
3 4
 
1.5%
4 4
 
1.5%
18 2
 
0.7%
8 2
 
0.7%
Other values (22) 29
 
10.7%
2023-12-09T22:14:53.459982image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 226
70.4%
1 23
 
7.2%
2 16
 
5.0%
5 15
 
4.7%
4 14
 
4.4%
3 11
 
3.4%
8 7
 
2.2%
6 5
 
1.6%
9 3
 
0.9%
7 1
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 321
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 226
70.4%
1 23
 
7.2%
2 16
 
5.0%
5 15
 
4.7%
4 14
 
4.4%
3 11
 
3.4%
8 7
 
2.2%
6 5
 
1.6%
9 3
 
0.9%
7 1
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
Common 321
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 226
70.4%
1 23
 
7.2%
2 16
 
5.0%
5 15
 
4.7%
4 14
 
4.4%
3 11
 
3.4%
8 7
 
2.2%
6 5
 
1.6%
9 3
 
0.9%
7 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 321
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 226
70.4%
1 23
 
7.2%
2 16
 
5.0%
5 15
 
4.7%
4 14
 
4.4%
3 11
 
3.4%
8 7
 
2.2%
6 5
 
1.6%
9 3
 
0.9%
7 1
 
0.3%

q16_c9_r1
Text

MISSING 

Distinct22
Distinct (%)10.8%
Missing796
Missing (%)79.6%
Memory size36.6 KiB
2023-12-09T22:14:53.609134image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.161764706
Min length1

Characters and Unicode

Total characters237
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)5.4%

Sample

1st row6
2nd row0
3rd row0
4th row0
5th row30
ValueCountFrequency (%)
0 152
74.5%
10 7
 
3.4%
1 6
 
2.9%
20 6
 
2.9%
25 5
 
2.5%
30 4
 
2.0%
12 3
 
1.5%
2 3
 
1.5%
6 3
 
1.5%
14 2
 
1.0%
Other values (12) 13
 
6.4%
2023-12-09T22:14:53.888058image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 170
71.7%
1 22
 
9.3%
2 19
 
8.0%
5 6
 
2.5%
3 6
 
2.5%
4 6
 
2.5%
6 4
 
1.7%
8 2
 
0.8%
9 1
 
0.4%
7 1
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 237
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 170
71.7%
1 22
 
9.3%
2 19
 
8.0%
5 6
 
2.5%
3 6
 
2.5%
4 6
 
2.5%
6 4
 
1.7%
8 2
 
0.8%
9 1
 
0.4%
7 1
 
0.4%

Most occurring scripts

ValueCountFrequency (%)
Common 237
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 170
71.7%
1 22
 
9.3%
2 19
 
8.0%
5 6
 
2.5%
3 6
 
2.5%
4 6
 
2.5%
6 4
 
1.7%
8 2
 
0.8%
9 1
 
0.4%
7 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 237
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 170
71.7%
1 22
 
9.3%
2 19
 
8.0%
5 6
 
2.5%
3 6
 
2.5%
4 6
 
2.5%
6 4
 
1.7%
8 2
 
0.8%
9 1
 
0.4%
7 1
 
0.4%

q16_c9_r2
Text

MISSING 

Distinct29
Distinct (%)14.2%
Missing796
Missing (%)79.6%
Memory size36.6 KiB
2023-12-09T22:14:54.045217image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.161764706
Min length1

Characters and Unicode

Total characters237
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)8.3%

Sample

1st row5
2nd row0
3rd row0
4th row32
5th row0
ValueCountFrequency (%)
0 151
74.0%
1 8
 
3.9%
5 5
 
2.5%
20 5
 
2.5%
2 3
 
1.5%
10 3
 
1.5%
40 2
 
1.0%
25 2
 
1.0%
42 2
 
1.0%
50 2
 
1.0%
Other values (19) 21
 
10.3%
2023-12-09T22:14:54.350788image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 166
70.0%
1 19
 
8.0%
5 15
 
6.3%
2 15
 
6.3%
4 9
 
3.8%
7 4
 
1.7%
3 4
 
1.7%
6 3
 
1.3%
9 1
 
0.4%
8 1
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 237
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 166
70.0%
1 19
 
8.0%
5 15
 
6.3%
2 15
 
6.3%
4 9
 
3.8%
7 4
 
1.7%
3 4
 
1.7%
6 3
 
1.3%
9 1
 
0.4%
8 1
 
0.4%

Most occurring scripts

ValueCountFrequency (%)
Common 237
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 166
70.0%
1 19
 
8.0%
5 15
 
6.3%
2 15
 
6.3%
4 9
 
3.8%
7 4
 
1.7%
3 4
 
1.7%
6 3
 
1.3%
9 1
 
0.4%
8 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 237
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 166
70.0%
1 19
 
8.0%
5 15
 
6.3%
2 15
 
6.3%
4 9
 
3.8%
7 4
 
1.7%
3 4
 
1.7%
6 3
 
1.3%
9 1
 
0.4%
8 1
 
0.4%

q16_c9_r3
Text

MISSING 

Distinct17
Distinct (%)8.3%
Missing796
Missing (%)79.6%
Memory size36.6 KiB
2023-12-09T22:14:54.492698image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.098039216
Min length1

Characters and Unicode

Total characters224
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)3.9%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 168
82.4%
1 5
 
2.5%
20 5
 
2.5%
10 4
 
2.0%
2 4
 
2.0%
5 3
 
1.5%
30 3
 
1.5%
8 2
 
1.0%
25 2
 
1.0%
45 1
 
0.5%
Other values (7) 7
 
3.4%
2023-12-09T22:14:54.763676image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 180
80.4%
1 12
 
5.4%
2 12
 
5.4%
5 8
 
3.6%
3 5
 
2.2%
8 2
 
0.9%
4 2
 
0.9%
9 1
 
0.4%
7 1
 
0.4%
6 1
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 224
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 180
80.4%
1 12
 
5.4%
2 12
 
5.4%
5 8
 
3.6%
3 5
 
2.2%
8 2
 
0.9%
4 2
 
0.9%
9 1
 
0.4%
7 1
 
0.4%
6 1
 
0.4%

Most occurring scripts

ValueCountFrequency (%)
Common 224
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 180
80.4%
1 12
 
5.4%
2 12
 
5.4%
5 8
 
3.6%
3 5
 
2.2%
8 2
 
0.9%
4 2
 
0.9%
9 1
 
0.4%
7 1
 
0.4%
6 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 224
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 180
80.4%
1 12
 
5.4%
2 12
 
5.4%
5 8
 
3.6%
3 5
 
2.2%
8 2
 
0.9%
4 2
 
0.9%
9 1
 
0.4%
7 1
 
0.4%
6 1
 
0.4%

q16_c9_r4
Text

MISSING 

Distinct27
Distinct (%)13.2%
Missing796
Missing (%)79.6%
Memory size36.6 KiB
2023-12-09T22:14:54.920657image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.161764706
Min length1

Characters and Unicode

Total characters237
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)6.9%

Sample

1st row0
2nd row0
3rd row0
4th row40
5th row0
ValueCountFrequency (%)
0 153
75.0%
10 6
 
2.9%
20 5
 
2.5%
3 4
 
2.0%
4 3
 
1.5%
1 3
 
1.5%
40 3
 
1.5%
9 3
 
1.5%
5 2
 
1.0%
2 2
 
1.0%
Other values (17) 20
 
9.8%
2023-12-09T22:14:55.225713image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 172
72.6%
1 17
 
7.2%
5 11
 
4.6%
2 8
 
3.4%
3 8
 
3.4%
4 8
 
3.4%
8 6
 
2.5%
9 4
 
1.7%
6 2
 
0.8%
7 1
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 237
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 172
72.6%
1 17
 
7.2%
5 11
 
4.6%
2 8
 
3.4%
3 8
 
3.4%
4 8
 
3.4%
8 6
 
2.5%
9 4
 
1.7%
6 2
 
0.8%
7 1
 
0.4%

Most occurring scripts

ValueCountFrequency (%)
Common 237
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 172
72.6%
1 17
 
7.2%
5 11
 
4.6%
2 8
 
3.4%
3 8
 
3.4%
4 8
 
3.4%
8 6
 
2.5%
9 4
 
1.7%
6 2
 
0.8%
7 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 237
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 172
72.6%
1 17
 
7.2%
5 11
 
4.6%
2 8
 
3.4%
3 8
 
3.4%
4 8
 
3.4%
8 6
 
2.5%
9 4
 
1.7%
6 2
 
0.8%
7 1
 
0.4%

q16_c10_r1
Text

MISSING 

Distinct21
Distinct (%)13.3%
Missing842
Missing (%)84.2%
Memory size35.4 KiB
2023-12-09T22:14:55.376568image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.151898734
Min length1

Characters and Unicode

Total characters182
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)7.6%

Sample

1st row6
2nd row0
3rd row0
4th row30
5th row25
ValueCountFrequency (%)
0 119
75.3%
10 6
 
3.8%
1 4
 
2.5%
25 4
 
2.5%
2 3
 
1.9%
20 3
 
1.9%
30 3
 
1.9%
6 2
 
1.3%
5 2
 
1.3%
11 1
 
0.6%
Other values (11) 11
 
7.0%
2023-12-09T22:14:56.020569image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 132
72.5%
1 16
 
8.8%
2 13
 
7.1%
5 6
 
3.3%
3 4
 
2.2%
4 4
 
2.2%
6 3
 
1.6%
8 2
 
1.1%
9 1
 
0.5%
7 1
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 182
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 132
72.5%
1 16
 
8.8%
2 13
 
7.1%
5 6
 
3.3%
3 4
 
2.2%
4 4
 
2.2%
6 3
 
1.6%
8 2
 
1.1%
9 1
 
0.5%
7 1
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
Common 182
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 132
72.5%
1 16
 
8.8%
2 13
 
7.1%
5 6
 
3.3%
3 4
 
2.2%
4 4
 
2.2%
6 3
 
1.6%
8 2
 
1.1%
9 1
 
0.5%
7 1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 182
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 132
72.5%
1 16
 
8.8%
2 13
 
7.1%
5 6
 
3.3%
3 4
 
2.2%
4 4
 
2.2%
6 3
 
1.6%
8 2
 
1.1%
9 1
 
0.5%
7 1
 
0.5%

q16_c10_r2
Text

MISSING 

Distinct22
Distinct (%)13.9%
Missing842
Missing (%)84.2%
Memory size35.4 KiB
2023-12-09T22:14:56.167672image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.126582278
Min length1

Characters and Unicode

Total characters178
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)8.9%

Sample

1st row5
2nd row0
3rd row32
4th row0
5th row42
ValueCountFrequency (%)
0 121
76.6%
1 7
 
4.4%
20 4
 
2.5%
2 3
 
1.9%
5 3
 
1.9%
50 2
 
1.3%
7 2
 
1.3%
42 2
 
1.3%
30 1
 
0.6%
16 1
 
0.6%
Other values (12) 12
 
7.6%
2023-12-09T22:14:56.447396image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 132
74.2%
2 13
 
7.3%
1 10
 
5.6%
5 9
 
5.1%
4 4
 
2.2%
7 3
 
1.7%
3 3
 
1.7%
6 2
 
1.1%
9 1
 
0.6%
8 1
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 178
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 132
74.2%
2 13
 
7.3%
1 10
 
5.6%
5 9
 
5.1%
4 4
 
2.2%
7 3
 
1.7%
3 3
 
1.7%
6 2
 
1.1%
9 1
 
0.6%
8 1
 
0.6%

Most occurring scripts

ValueCountFrequency (%)
Common 178
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 132
74.2%
2 13
 
7.3%
1 10
 
5.6%
5 9
 
5.1%
4 4
 
2.2%
7 3
 
1.7%
3 3
 
1.7%
6 2
 
1.1%
9 1
 
0.6%
8 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 178
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 132
74.2%
2 13
 
7.3%
1 10
 
5.6%
5 9
 
5.1%
4 4
 
2.2%
7 3
 
1.7%
3 3
 
1.7%
6 2
 
1.1%
9 1
 
0.6%
8 1
 
0.6%

q16_c10_r3
Text

MISSING 

Distinct17
Distinct (%)10.8%
Missing842
Missing (%)84.2%
Memory size35.4 KiB
2023-12-09T22:14:56.588044image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.094936709
Min length1

Characters and Unicode

Total characters173
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)7.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 131
82.9%
1 4
 
2.5%
20 4
 
2.5%
10 3
 
1.9%
2 3
 
1.9%
25 2
 
1.3%
4 1
 
0.6%
36 1
 
0.6%
7 1
 
0.6%
12 1
 
0.6%
Other values (7) 7
 
4.4%
2023-12-09T22:14:56.850706image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 139
80.3%
2 10
 
5.8%
1 9
 
5.2%
5 5
 
2.9%
3 3
 
1.7%
4 3
 
1.7%
8 1
 
0.6%
9 1
 
0.6%
7 1
 
0.6%
6 1
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 173
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 139
80.3%
2 10
 
5.8%
1 9
 
5.2%
5 5
 
2.9%
3 3
 
1.7%
4 3
 
1.7%
8 1
 
0.6%
9 1
 
0.6%
7 1
 
0.6%
6 1
 
0.6%

Most occurring scripts

ValueCountFrequency (%)
Common 173
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 139
80.3%
2 10
 
5.8%
1 9
 
5.2%
5 5
 
2.9%
3 3
 
1.7%
4 3
 
1.7%
8 1
 
0.6%
9 1
 
0.6%
7 1
 
0.6%
6 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 173
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 139
80.3%
2 10
 
5.8%
1 9
 
5.2%
5 5
 
2.9%
3 3
 
1.7%
4 3
 
1.7%
8 1
 
0.6%
9 1
 
0.6%
7 1
 
0.6%
6 1
 
0.6%

q16_c10_r4
Text

MISSING 

Distinct21
Distinct (%)13.3%
Missing842
Missing (%)84.2%
Memory size35.4 KiB
2023-12-09T22:14:56.999515image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.126582278
Min length1

Characters and Unicode

Total characters178
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)8.2%

Sample

1st row0
2nd row0
3rd row40
4th row0
5th row0
ValueCountFrequency (%)
0 125
79.1%
20 4
 
2.5%
4 3
 
1.9%
3 3
 
1.9%
8 3
 
1.9%
10 3
 
1.9%
1 2
 
1.3%
40 2
 
1.3%
58 1
 
0.6%
13 1
 
0.6%
Other values (11) 11
 
7.0%
2023-12-09T22:14:57.296743image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 137
77.0%
1 11
 
6.2%
3 7
 
3.9%
4 6
 
3.4%
2 5
 
2.8%
8 5
 
2.8%
5 3
 
1.7%
6 2
 
1.1%
7 1
 
0.6%
9 1
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 178
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 137
77.0%
1 11
 
6.2%
3 7
 
3.9%
4 6
 
3.4%
2 5
 
2.8%
8 5
 
2.8%
5 3
 
1.7%
6 2
 
1.1%
7 1
 
0.6%
9 1
 
0.6%

Most occurring scripts

ValueCountFrequency (%)
Common 178
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 137
77.0%
1 11
 
6.2%
3 7
 
3.9%
4 6
 
3.4%
2 5
 
2.8%
8 5
 
2.8%
5 3
 
1.7%
6 2
 
1.1%
7 1
 
0.6%
9 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 178
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 137
77.0%
1 11
 
6.2%
3 7
 
3.9%
4 6
 
3.4%
2 5
 
2.8%
8 5
 
2.8%
5 3
 
1.7%
6 2
 
1.1%
7 1
 
0.6%
9 1
 
0.6%

q16_c11_r1
Text

MISSING 

Distinct14
Distinct (%)12.4%
Missing887
Missing (%)88.7%
Memory size34.3 KiB
2023-12-09T22:14:57.438843image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.17699115
Min length1

Characters and Unicode

Total characters133
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)5.3%

Sample

1st row6
2nd row0
3rd row30
4th row0
5th row0
ValueCountFrequency (%)
0 85
75.2%
10 5
 
4.4%
1 4
 
3.5%
25 3
 
2.7%
20 3
 
2.7%
30 3
 
2.7%
12 2
 
1.8%
6 2
 
1.8%
46 1
 
0.9%
11 1
 
0.9%
Other values (4) 4
 
3.5%
2023-12-09T22:14:57.693496image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 96
72.2%
1 14
 
10.5%
2 10
 
7.5%
3 4
 
3.0%
5 3
 
2.3%
6 3
 
2.3%
4 2
 
1.5%
8 1
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 133
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 96
72.2%
1 14
 
10.5%
2 10
 
7.5%
3 4
 
3.0%
5 3
 
2.3%
6 3
 
2.3%
4 2
 
1.5%
8 1
 
0.8%

Most occurring scripts

ValueCountFrequency (%)
Common 133
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 96
72.2%
1 14
 
10.5%
2 10
 
7.5%
3 4
 
3.0%
5 3
 
2.3%
6 3
 
2.3%
4 2
 
1.5%
8 1
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 133
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 96
72.2%
1 14
 
10.5%
2 10
 
7.5%
3 4
 
3.0%
5 3
 
2.3%
6 3
 
2.3%
4 2
 
1.5%
8 1
 
0.8%

q16_c11_r2
Text

MISSING 

Distinct16
Distinct (%)14.2%
Missing887
Missing (%)88.7%
Memory size34.3 KiB
2023-12-09T22:14:57.828943image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.10619469
Min length1

Characters and Unicode

Total characters125
Distinct characters9
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)10.6%

Sample

1st row5
2nd row0
3rd row0
4th row0
5th row2
ValueCountFrequency (%)
0 91
80.5%
1 4
 
3.5%
20 3
 
2.7%
5 3
 
2.7%
70 1
 
0.9%
35 1
 
0.9%
40 1
 
0.9%
42 1
 
0.9%
30 1
 
0.9%
25 1
 
0.9%
Other values (6) 6
 
5.3%
2023-12-09T22:14:58.087608image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 98
78.4%
2 6
 
4.8%
5 6
 
4.8%
1 5
 
4.0%
4 3
 
2.4%
7 2
 
1.6%
3 2
 
1.6%
6 2
 
1.6%
8 1
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 125
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 98
78.4%
2 6
 
4.8%
5 6
 
4.8%
1 5
 
4.0%
4 3
 
2.4%
7 2
 
1.6%
3 2
 
1.6%
6 2
 
1.6%
8 1
 
0.8%

Most occurring scripts

ValueCountFrequency (%)
Common 125
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 98
78.4%
2 6
 
4.8%
5 6
 
4.8%
1 5
 
4.0%
4 3
 
2.4%
7 2
 
1.6%
3 2
 
1.6%
6 2
 
1.6%
8 1
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 125
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 98
78.4%
2 6
 
4.8%
5 6
 
4.8%
1 5
 
4.0%
4 3
 
2.4%
7 2
 
1.6%
3 2
 
1.6%
6 2
 
1.6%
8 1
 
0.8%

q16_c11_r3
Text

MISSING 

Distinct13
Distinct (%)11.5%
Missing887
Missing (%)88.7%
Memory size34.3 KiB
2023-12-09T22:14:58.222355image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.115044248
Min length1

Characters and Unicode

Total characters126
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)7.1%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row12
ValueCountFrequency (%)
0 96
85.0%
20 3
 
2.7%
12 2
 
1.8%
10 2
 
1.8%
1 2
 
1.8%
25 1
 
0.9%
36 1
 
0.9%
4 1
 
0.9%
45 1
 
0.9%
8 1
 
0.9%
Other values (3) 3
 
2.7%
2023-12-09T22:14:58.485720image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 102
81.0%
1 7
 
5.6%
2 6
 
4.8%
5 3
 
2.4%
3 3
 
2.4%
4 3
 
2.4%
6 1
 
0.8%
8 1
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 126
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 102
81.0%
1 7
 
5.6%
2 6
 
4.8%
5 3
 
2.4%
3 3
 
2.4%
4 3
 
2.4%
6 1
 
0.8%
8 1
 
0.8%

Most occurring scripts

ValueCountFrequency (%)
Common 126
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 102
81.0%
1 7
 
5.6%
2 6
 
4.8%
5 3
 
2.4%
3 3
 
2.4%
4 3
 
2.4%
6 1
 
0.8%
8 1
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 126
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 102
81.0%
1 7
 
5.6%
2 6
 
4.8%
5 3
 
2.4%
3 3
 
2.4%
4 3
 
2.4%
6 1
 
0.8%
8 1
 
0.8%

q16_c11_r4
Text

MISSING 

Distinct16
Distinct (%)14.2%
Missing887
Missing (%)88.7%
Memory size34.3 KiB
2023-12-09T22:14:58.626761image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.132743363
Min length1

Characters and Unicode

Total characters128
Distinct characters9
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)10.6%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row4
ValueCountFrequency (%)
0 94
83.2%
20 3
 
2.7%
3 2
 
1.8%
10 2
 
1.8%
18 1
 
0.9%
35 1
 
0.9%
40 1
 
0.9%
117 1
 
0.9%
30 1
 
0.9%
12 1
 
0.9%
Other values (6) 6
 
5.3%
2023-12-09T22:14:58.905227image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 102
79.7%
1 7
 
5.5%
2 4
 
3.1%
3 4
 
3.1%
8 3
 
2.3%
4 3
 
2.3%
5 2
 
1.6%
6 2
 
1.6%
7 1
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 128
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 102
79.7%
1 7
 
5.5%
2 4
 
3.1%
3 4
 
3.1%
8 3
 
2.3%
4 3
 
2.3%
5 2
 
1.6%
6 2
 
1.6%
7 1
 
0.8%

Most occurring scripts

ValueCountFrequency (%)
Common 128
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 102
79.7%
1 7
 
5.5%
2 4
 
3.1%
3 4
 
3.1%
8 3
 
2.3%
4 3
 
2.3%
5 2
 
1.6%
6 2
 
1.6%
7 1
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 128
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 102
79.7%
1 7
 
5.5%
2 4
 
3.1%
3 4
 
3.1%
8 3
 
2.3%
4 3
 
2.3%
5 2
 
1.6%
6 2
 
1.6%
7 1
 
0.8%

q16_c12_r1
Text

MISSING 

Distinct11
Distinct (%)12.5%
Missing912
Missing (%)91.2%
Memory size33.6 KiB
2023-12-09T22:14:59.038234image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.159090909
Min length1

Characters and Unicode

Total characters102
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)6.8%

Sample

1st row0
2nd row0
3rd row0
4th row20
5th row0
ValueCountFrequency (%)
0 70
79.5%
10 4
 
4.5%
20 3
 
3.4%
30 3
 
3.4%
1 2
 
2.3%
12 1
 
1.1%
46 1
 
1.1%
6 1
 
1.1%
11 1
 
1.1%
24 1
 
1.1%
2023-12-09T22:14:59.299213image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 80
78.4%
1 9
 
8.8%
2 5
 
4.9%
3 4
 
3.9%
4 2
 
2.0%
6 2
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 102
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 80
78.4%
1 9
 
8.8%
2 5
 
4.9%
3 4
 
3.9%
4 2
 
2.0%
6 2
 
2.0%

Most occurring scripts

ValueCountFrequency (%)
Common 102
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 80
78.4%
1 9
 
8.8%
2 5
 
4.9%
3 4
 
3.9%
4 2
 
2.0%
6 2
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 102
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 80
78.4%
1 9
 
8.8%
2 5
 
4.9%
3 4
 
3.9%
4 2
 
2.0%
6 2
 
2.0%

q16_c12_r2
Text

MISSING 

Distinct12
Distinct (%)13.6%
Missing912
Missing (%)91.2%
Memory size33.6 KiB
2023-12-09T22:14:59.430708image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.113636364
Min length1

Characters and Unicode

Total characters98
Distinct characters9
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)9.1%

Sample

1st row0
2nd row0
3rd row60
4th row20
5th row0
ValueCountFrequency (%)
0 73
83.0%
20 3
 
3.4%
5 2
 
2.3%
1 2
 
2.3%
25 1
 
1.1%
45 1
 
1.1%
16 1
 
1.1%
8 1
 
1.1%
30 1
 
1.1%
35 1
 
1.1%
Other values (2) 2
 
2.3%
2023-12-09T22:14:59.683484image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 79
80.6%
5 5
 
5.1%
2 4
 
4.1%
1 3
 
3.1%
6 2
 
2.0%
3 2
 
2.0%
4 1
 
1.0%
8 1
 
1.0%
7 1
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 98
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 79
80.6%
5 5
 
5.1%
2 4
 
4.1%
1 3
 
3.1%
6 2
 
2.0%
3 2
 
2.0%
4 1
 
1.0%
8 1
 
1.0%
7 1
 
1.0%

Most occurring scripts

ValueCountFrequency (%)
Common 98
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 79
80.6%
5 5
 
5.1%
2 4
 
4.1%
1 3
 
3.1%
6 2
 
2.0%
3 2
 
2.0%
4 1
 
1.0%
8 1
 
1.0%
7 1
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 98
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 79
80.6%
5 5
 
5.1%
2 4
 
4.1%
1 3
 
3.1%
6 2
 
2.0%
3 2
 
2.0%
4 1
 
1.0%
8 1
 
1.0%
7 1
 
1.0%

q16_c12_r3
Text

MISSING 

Distinct10
Distinct (%)11.4%
Missing912
Missing (%)91.2%
Memory size33.6 KiB
2023-12-09T22:14:59.808181image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.113636364
Min length1

Characters and Unicode

Total characters98
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)8.0%

Sample

1st row0
2nd row0
3rd row0
4th row20
5th row0
ValueCountFrequency (%)
0 75
85.2%
20 4
 
4.5%
1 2
 
2.3%
25 1
 
1.1%
36 1
 
1.1%
45 1
 
1.1%
8 1
 
1.1%
30 1
 
1.1%
10 1
 
1.1%
35 1
 
1.1%
2023-12-09T22:15:00.051488image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 81
82.7%
2 5
 
5.1%
1 3
 
3.1%
5 3
 
3.1%
3 3
 
3.1%
6 1
 
1.0%
4 1
 
1.0%
8 1
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 98
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 81
82.7%
2 5
 
5.1%
1 3
 
3.1%
5 3
 
3.1%
3 3
 
3.1%
6 1
 
1.0%
4 1
 
1.0%
8 1
 
1.0%

Most occurring scripts

ValueCountFrequency (%)
Common 98
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 81
82.7%
2 5
 
5.1%
1 3
 
3.1%
5 3
 
3.1%
3 3
 
3.1%
6 1
 
1.0%
4 1
 
1.0%
8 1
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 98
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 81
82.7%
2 5
 
5.1%
1 3
 
3.1%
5 3
 
3.1%
3 3
 
3.1%
6 1
 
1.0%
4 1
 
1.0%
8 1
 
1.0%

q16_c12_r4
Text

MISSING 

Distinct13
Distinct (%)14.8%
Missing912
Missing (%)91.2%
Memory size33.6 KiB
2023-12-09T22:15:00.182835image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.136363636
Min length1

Characters and Unicode

Total characters100
Distinct characters9
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)11.4%

Sample

1st row0
2nd row0
3rd row60
4th row0
5th row0
ValueCountFrequency (%)
0 73
83.0%
20 3
 
3.4%
3 2
 
2.3%
6 1
 
1.1%
17 1
 
1.1%
8 1
 
1.1%
30 1
 
1.1%
18 1
 
1.1%
10 1
 
1.1%
117 1
 
1.1%
Other values (3) 3
 
3.4%
2023-12-09T22:15:00.470836image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 80
80.0%
1 5
 
5.0%
3 4
 
4.0%
2 3
 
3.0%
6 2
 
2.0%
7 2
 
2.0%
8 2
 
2.0%
4 1
 
1.0%
5 1
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 100
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 80
80.0%
1 5
 
5.0%
3 4
 
4.0%
2 3
 
3.0%
6 2
 
2.0%
7 2
 
2.0%
8 2
 
2.0%
4 1
 
1.0%
5 1
 
1.0%

Most occurring scripts

ValueCountFrequency (%)
Common 100
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 80
80.0%
1 5
 
5.0%
3 4
 
4.0%
2 3
 
3.0%
6 2
 
2.0%
7 2
 
2.0%
8 2
 
2.0%
4 1
 
1.0%
5 1
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 100
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 80
80.0%
1 5
 
5.0%
3 4
 
4.0%
2 3
 
3.0%
6 2
 
2.0%
7 2
 
2.0%
8 2
 
2.0%
4 1
 
1.0%
5 1
 
1.0%

q16_c13_r1
Text

MISSING 

Distinct10
Distinct (%)15.2%
Missing934
Missing (%)93.4%
Memory size33.1 KiB
2023-12-09T22:15:00.600447image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.166666667
Min length1

Characters and Unicode

Total characters77
Distinct characters7
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)9.1%

Sample

1st row0
2nd row0
3rd row20
4th row0
5th row0
ValueCountFrequency (%)
0 52
78.8%
10 4
 
6.1%
20 2
 
3.0%
1 2
 
3.0%
25 1
 
1.5%
46 1
 
1.5%
2 1
 
1.5%
11 1
 
1.5%
30 1
 
1.5%
24 1
 
1.5%
2023-12-09T22:15:00.853107image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 59
76.6%
1 8
 
10.4%
2 5
 
6.5%
4 2
 
2.6%
5 1
 
1.3%
6 1
 
1.3%
3 1
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 77
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 59
76.6%
1 8
 
10.4%
2 5
 
6.5%
4 2
 
2.6%
5 1
 
1.3%
6 1
 
1.3%
3 1
 
1.3%

Most occurring scripts

ValueCountFrequency (%)
Common 77
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 59
76.6%
1 8
 
10.4%
2 5
 
6.5%
4 2
 
2.6%
5 1
 
1.3%
6 1
 
1.3%
3 1
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 77
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 59
76.6%
1 8
 
10.4%
2 5
 
6.5%
4 2
 
2.6%
5 1
 
1.3%
6 1
 
1.3%
3 1
 
1.3%

q16_c13_r2
Text

MISSING 

Distinct10
Distinct (%)15.2%
Missing934
Missing (%)93.4%
Memory size33.1 KiB
2023-12-09T22:15:00.980865image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.106060606
Min length1

Characters and Unicode

Total characters73
Distinct characters9
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)10.6%

Sample

1st row0
2nd row0
3rd row20
4th row1
5th row0
ValueCountFrequency (%)
0 54
81.8%
1 3
 
4.5%
20 2
 
3.0%
25 1
 
1.5%
2 1
 
1.5%
45 1
 
1.5%
16 1
 
1.5%
8 1
 
1.5%
35 1
 
1.5%
70 1
 
1.5%
2023-12-09T22:15:01.233572image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 57
78.1%
1 4
 
5.5%
2 4
 
5.5%
5 3
 
4.1%
4 1
 
1.4%
6 1
 
1.4%
8 1
 
1.4%
3 1
 
1.4%
7 1
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 73
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 57
78.1%
1 4
 
5.5%
2 4
 
5.5%
5 3
 
4.1%
4 1
 
1.4%
6 1
 
1.4%
8 1
 
1.4%
3 1
 
1.4%
7 1
 
1.4%

Most occurring scripts

ValueCountFrequency (%)
Common 73
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 57
78.1%
1 4
 
5.5%
2 4
 
5.5%
5 3
 
4.1%
4 1
 
1.4%
6 1
 
1.4%
8 1
 
1.4%
3 1
 
1.4%
7 1
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 73
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 57
78.1%
1 4
 
5.5%
2 4
 
5.5%
5 3
 
4.1%
4 1
 
1.4%
6 1
 
1.4%
8 1
 
1.4%
3 1
 
1.4%
7 1
 
1.4%

q16_c13_r3
Text

MISSING 

Distinct7
Distinct (%)10.6%
Missing934
Missing (%)93.4%
Memory size33.1 KiB
2023-12-09T22:15:01.359590image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.106060606
Min length1

Characters and Unicode

Total characters73
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)7.6%

Sample

1st row0
2nd row0
3rd row20
4th row0
5th row35
ValueCountFrequency (%)
0 58
87.9%
20 3
 
4.5%
25 1
 
1.5%
36 1
 
1.5%
2 1
 
1.5%
45 1
 
1.5%
35 1
 
1.5%
2023-12-09T22:15:01.608882image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 61
83.6%
2 5
 
6.8%
5 3
 
4.1%
3 2
 
2.7%
6 1
 
1.4%
4 1
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 73
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 61
83.6%
2 5
 
6.8%
5 3
 
4.1%
3 2
 
2.7%
6 1
 
1.4%
4 1
 
1.4%

Most occurring scripts

ValueCountFrequency (%)
Common 73
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 61
83.6%
2 5
 
6.8%
5 3
 
4.1%
3 2
 
2.7%
6 1
 
1.4%
4 1
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 73
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 61
83.6%
2 5
 
6.8%
5 3
 
4.1%
3 2
 
2.7%
6 1
 
1.4%
4 1
 
1.4%

q16_c13_r4
Text

MISSING 

Distinct11
Distinct (%)16.7%
Missing934
Missing (%)93.4%
Memory size33.1 KiB
2023-12-09T22:15:01.742928image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.166666667
Min length1

Characters and Unicode

Total characters77
Distinct characters9
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)12.1%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 52
78.8%
20 4
 
6.1%
18 2
 
3.0%
2 1
 
1.5%
6 1
 
1.5%
8 1
 
1.5%
10 1
 
1.5%
117 1
 
1.5%
3 1
 
1.5%
40 1
 
1.5%
2023-12-09T22:15:02.012379image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 58
75.3%
2 5
 
6.5%
1 5
 
6.5%
8 3
 
3.9%
3 2
 
2.6%
6 1
 
1.3%
7 1
 
1.3%
4 1
 
1.3%
5 1
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 77
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 58
75.3%
2 5
 
6.5%
1 5
 
6.5%
8 3
 
3.9%
3 2
 
2.6%
6 1
 
1.3%
7 1
 
1.3%
4 1
 
1.3%
5 1
 
1.3%

Most occurring scripts

ValueCountFrequency (%)
Common 77
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 58
75.3%
2 5
 
6.5%
1 5
 
6.5%
8 3
 
3.9%
3 2
 
2.6%
6 1
 
1.3%
7 1
 
1.3%
4 1
 
1.3%
5 1
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 77
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 58
75.3%
2 5
 
6.5%
1 5
 
6.5%
8 3
 
3.9%
3 2
 
2.6%
6 1
 
1.3%
7 1
 
1.3%
4 1
 
1.3%
5 1
 
1.3%

q16_c14_r1
Text

MISSING 

Distinct10
Distinct (%)18.9%
Missing947
Missing (%)94.7%
Memory size32.7 KiB
2023-12-09T22:15:02.136048image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.20754717
Min length1

Characters and Unicode

Total characters64
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)9.4%

Sample

1st row0
2nd row0
3rd row20
4th row0
5th row0
ValueCountFrequency (%)
0 39
73.6%
10 3
 
5.7%
20 2
 
3.8%
30 2
 
3.8%
1 2
 
3.8%
12 1
 
1.9%
46 1
 
1.9%
2 1
 
1.9%
11 1
 
1.9%
24 1
 
1.9%
2023-12-09T22:15:02.377070image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 46
71.9%
1 8
 
12.5%
2 5
 
7.8%
3 2
 
3.1%
4 2
 
3.1%
6 1
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 64
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 46
71.9%
1 8
 
12.5%
2 5
 
7.8%
3 2
 
3.1%
4 2
 
3.1%
6 1
 
1.6%

Most occurring scripts

ValueCountFrequency (%)
Common 64
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 46
71.9%
1 8
 
12.5%
2 5
 
7.8%
3 2
 
3.1%
4 2
 
3.1%
6 1
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 64
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 46
71.9%
1 8
 
12.5%
2 5
 
7.8%
3 2
 
3.1%
4 2
 
3.1%
6 1
 
1.6%

q16_c14_r2
Text

MISSING 

Distinct11
Distinct (%)20.8%
Missing947
Missing (%)94.7%
Memory size32.7 KiB
2023-12-09T22:15:02.504125image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.150943396
Min length1

Characters and Unicode

Total characters61
Distinct characters9
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)17.0%

Sample

1st row0
2nd row0
3rd row20
4th row1
5th row0
ValueCountFrequency (%)
0 42
79.2%
20 2
 
3.8%
25 1
 
1.9%
2 1
 
1.9%
45 1
 
1.9%
16 1
 
1.9%
8 1
 
1.9%
10 1
 
1.9%
1 1
 
1.9%
35 1
 
1.9%
2023-12-09T22:15:02.760273image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 46
75.4%
2 4
 
6.6%
5 3
 
4.9%
1 3
 
4.9%
4 1
 
1.6%
6 1
 
1.6%
8 1
 
1.6%
3 1
 
1.6%
7 1
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 61
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 46
75.4%
2 4
 
6.6%
5 3
 
4.9%
1 3
 
4.9%
4 1
 
1.6%
6 1
 
1.6%
8 1
 
1.6%
3 1
 
1.6%
7 1
 
1.6%

Most occurring scripts

ValueCountFrequency (%)
Common 61
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 46
75.4%
2 4
 
6.6%
5 3
 
4.9%
1 3
 
4.9%
4 1
 
1.6%
6 1
 
1.6%
8 1
 
1.6%
3 1
 
1.6%
7 1
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 61
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 46
75.4%
2 4
 
6.6%
5 3
 
4.9%
1 3
 
4.9%
4 1
 
1.6%
6 1
 
1.6%
8 1
 
1.6%
3 1
 
1.6%
7 1
 
1.6%

q16_c14_r3
Text

MISSING 

Distinct7
Distinct (%)13.2%
Missing947
Missing (%)94.7%
Memory size32.7 KiB
2023-12-09T22:15:02.880019image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.113207547
Min length1

Characters and Unicode

Total characters59
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)9.4%

Sample

1st row0
2nd row0
3rd row20
4th row0
5th row35
ValueCountFrequency (%)
0 46
86.8%
20 2
 
3.8%
25 1
 
1.9%
36 1
 
1.9%
2 1
 
1.9%
45 1
 
1.9%
35 1
 
1.9%
2023-12-09T22:15:03.113187image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 48
81.4%
2 4
 
6.8%
5 3
 
5.1%
3 2
 
3.4%
6 1
 
1.7%
4 1
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 59
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 48
81.4%
2 4
 
6.8%
5 3
 
5.1%
3 2
 
3.4%
6 1
 
1.7%
4 1
 
1.7%

Most occurring scripts

ValueCountFrequency (%)
Common 59
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 48
81.4%
2 4
 
6.8%
5 3
 
5.1%
3 2
 
3.4%
6 1
 
1.7%
4 1
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 59
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 48
81.4%
2 4
 
6.8%
5 3
 
5.1%
3 2
 
3.4%
6 1
 
1.7%
4 1
 
1.7%

q16_c14_r4
Text

MISSING 

Distinct10
Distinct (%)18.9%
Missing947
Missing (%)94.7%
Memory size32.7 KiB
2023-12-09T22:15:03.242978image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.150943396
Min length1

Characters and Unicode

Total characters61
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)15.1%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 41
77.4%
20 4
 
7.5%
2 1
 
1.9%
6 1
 
1.9%
15 1
 
1.9%
8 1
 
1.9%
18 1
 
1.9%
3 1
 
1.9%
40 1
 
1.9%
35 1
 
1.9%
2023-12-09T22:15:03.486110image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 46
75.4%
2 5
 
8.2%
1 2
 
3.3%
5 2
 
3.3%
8 2
 
3.3%
3 2
 
3.3%
6 1
 
1.6%
4 1
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 61
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 46
75.4%
2 5
 
8.2%
1 2
 
3.3%
5 2
 
3.3%
8 2
 
3.3%
3 2
 
3.3%
6 1
 
1.6%
4 1
 
1.6%

Most occurring scripts

ValueCountFrequency (%)
Common 61
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 46
75.4%
2 5
 
8.2%
1 2
 
3.3%
5 2
 
3.3%
8 2
 
3.3%
3 2
 
3.3%
6 1
 
1.6%
4 1
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 61
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 46
75.4%
2 5
 
8.2%
1 2
 
3.3%
5 2
 
3.3%
8 2
 
3.3%
3 2
 
3.3%
6 1
 
1.6%
4 1
 
1.6%

q16_c15_r1
Text

MISSING 

Distinct6
Distinct (%)15.0%
Missing960
Missing (%)96.0%
Memory size32.4 KiB
2023-12-09T22:15:03.613410image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.1
Min length1

Characters and Unicode

Total characters44
Distinct characters7
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)12.5%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 35
87.5%
12 1
 
2.5%
8 1
 
2.5%
20 1
 
2.5%
30 1
 
2.5%
46 1
 
2.5%
2023-12-09T22:15:03.876163image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 37
84.1%
2 2
 
4.5%
1 1
 
2.3%
8 1
 
2.3%
3 1
 
2.3%
4 1
 
2.3%
6 1
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 44
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 37
84.1%
2 2
 
4.5%
1 1
 
2.3%
8 1
 
2.3%
3 1
 
2.3%
4 1
 
2.3%
6 1
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
Common 44
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 37
84.1%
2 2
 
4.5%
1 1
 
2.3%
8 1
 
2.3%
3 1
 
2.3%
4 1
 
2.3%
6 1
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 44
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 37
84.1%
2 2
 
4.5%
1 1
 
2.3%
8 1
 
2.3%
3 1
 
2.3%
4 1
 
2.3%
6 1
 
2.3%

q16_c15_r2
Text

MISSING 

Distinct9
Distinct (%)22.5%
Missing960
Missing (%)96.0%
Memory size32.4 KiB
2023-12-09T22:15:04.003918image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.15
Min length1

Characters and Unicode

Total characters46
Distinct characters9
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)20.0%

Sample

1st row0
2nd row0
3rd row1
4th row0
5th row0
ValueCountFrequency (%)
0 32
80.0%
45 1
 
2.5%
16 1
 
2.5%
8 1
 
2.5%
20 1
 
2.5%
10 1
 
2.5%
1 1
 
2.5%
35 1
 
2.5%
70 1
 
2.5%
2023-12-09T22:15:04.254434image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 35
76.1%
1 3
 
6.5%
5 2
 
4.3%
4 1
 
2.2%
6 1
 
2.2%
8 1
 
2.2%
2 1
 
2.2%
3 1
 
2.2%
7 1
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 46
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 35
76.1%
1 3
 
6.5%
5 2
 
4.3%
4 1
 
2.2%
6 1
 
2.2%
8 1
 
2.2%
2 1
 
2.2%
3 1
 
2.2%
7 1
 
2.2%

Most occurring scripts

ValueCountFrequency (%)
Common 46
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 35
76.1%
1 3
 
6.5%
5 2
 
4.3%
4 1
 
2.2%
6 1
 
2.2%
8 1
 
2.2%
2 1
 
2.2%
3 1
 
2.2%
7 1
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 46
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 35
76.1%
1 3
 
6.5%
5 2
 
4.3%
4 1
 
2.2%
6 1
 
2.2%
8 1
 
2.2%
2 1
 
2.2%
3 1
 
2.2%
7 1
 
2.2%

q16_c15_r3
Text

MISSING 

Distinct5
Distinct (%)12.5%
Missing960
Missing (%)96.0%
Memory size32.4 KiB
2023-12-09T22:15:04.372573image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.1
Min length1

Characters and Unicode

Total characters44
Distinct characters7
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)10.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 36
90.0%
36 1
 
2.5%
45 1
 
2.5%
16 1
 
2.5%
20 1
 
2.5%
2023-12-09T22:15:04.615058image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 37
84.1%
6 2
 
4.5%
3 1
 
2.3%
4 1
 
2.3%
5 1
 
2.3%
1 1
 
2.3%
2 1
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 44
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 37
84.1%
6 2
 
4.5%
3 1
 
2.3%
4 1
 
2.3%
5 1
 
2.3%
1 1
 
2.3%
2 1
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
Common 44
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 37
84.1%
6 2
 
4.5%
3 1
 
2.3%
4 1
 
2.3%
5 1
 
2.3%
1 1
 
2.3%
2 1
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 44
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 37
84.1%
6 2
 
4.5%
3 1
 
2.3%
4 1
 
2.3%
5 1
 
2.3%
1 1
 
2.3%
2 1
 
2.3%

q16_c15_r4
Text

MISSING 

Distinct9
Distinct (%)22.5%
Missing960
Missing (%)96.0%
Memory size32.4 KiB
2023-12-09T22:15:04.737243image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.15
Min length1

Characters and Unicode

Total characters46
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)17.5%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 31
77.5%
20 2
 
5.0%
6 1
 
2.5%
11 1
 
2.5%
8 1
 
2.5%
18 1
 
2.5%
3 1
 
2.5%
40 1
 
2.5%
35 1
 
2.5%
2023-12-09T22:15:05.451236image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 34
73.9%
1 3
 
6.5%
2 2
 
4.3%
8 2
 
4.3%
3 2
 
4.3%
6 1
 
2.2%
4 1
 
2.2%
5 1
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 46
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 34
73.9%
1 3
 
6.5%
2 2
 
4.3%
8 2
 
4.3%
3 2
 
4.3%
6 1
 
2.2%
4 1
 
2.2%
5 1
 
2.2%

Most occurring scripts

ValueCountFrequency (%)
Common 46
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 34
73.9%
1 3
 
6.5%
2 2
 
4.3%
8 2
 
4.3%
3 2
 
4.3%
6 1
 
2.2%
4 1
 
2.2%
5 1
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 46
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 34
73.9%
1 3
 
6.5%
2 2
 
4.3%
8 2
 
4.3%
3 2
 
4.3%
6 1
 
2.2%
4 1
 
2.2%
5 1
 
2.2%

q16_c16_r1
Text

MISSING 

Distinct3
Distinct (%)9.7%
Missing969
Missing (%)96.9%
Memory size32.2 KiB
2023-12-09T22:15:05.570243image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.064516129
Min length1

Characters and Unicode

Total characters33
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)6.5%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 29
93.5%
20 1
 
3.2%
46 1
 
3.2%
2023-12-09T22:15:05.810956image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 30
90.9%
2 1
 
3.0%
4 1
 
3.0%
6 1
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 33
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 30
90.9%
2 1
 
3.0%
4 1
 
3.0%
6 1
 
3.0%

Most occurring scripts

ValueCountFrequency (%)
Common 33
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 30
90.9%
2 1
 
3.0%
4 1
 
3.0%
6 1
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 33
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 30
90.9%
2 1
 
3.0%
4 1
 
3.0%
6 1
 
3.0%

q16_c16_r2
Text

MISSING 

Distinct7
Distinct (%)22.6%
Missing969
Missing (%)96.9%
Memory size32.2 KiB
2023-12-09T22:15:05.934675image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.129032258
Min length1

Characters and Unicode

Total characters35
Distinct characters7
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)19.4%

Sample

1st row0
2nd row1
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 25
80.6%
8 1
 
3.2%
20 1
 
3.2%
10 1
 
3.2%
1 1
 
3.2%
35 1
 
3.2%
70 1
 
3.2%
2023-12-09T22:15:06.178083image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 28
80.0%
1 2
 
5.7%
8 1
 
2.9%
2 1
 
2.9%
3 1
 
2.9%
5 1
 
2.9%
7 1
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 35
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 28
80.0%
1 2
 
5.7%
8 1
 
2.9%
2 1
 
2.9%
3 1
 
2.9%
5 1
 
2.9%
7 1
 
2.9%

Most occurring scripts

ValueCountFrequency (%)
Common 35
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 28
80.0%
1 2
 
5.7%
8 1
 
2.9%
2 1
 
2.9%
3 1
 
2.9%
5 1
 
2.9%
7 1
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 35
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 28
80.0%
1 2
 
5.7%
8 1
 
2.9%
2 1
 
2.9%
3 1
 
2.9%
5 1
 
2.9%
7 1
 
2.9%

q16_c16_r3
Text

MISSING 

Distinct3
Distinct (%)9.7%
Missing969
Missing (%)96.9%
Memory size32.2 KiB
2023-12-09T22:15:06.290334image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.064516129
Min length1

Characters and Unicode

Total characters33
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)6.5%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 29
93.5%
36 1
 
3.2%
20 1
 
3.2%
2023-12-09T22:15:06.525994image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 30
90.9%
3 1
 
3.0%
6 1
 
3.0%
2 1
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 33
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 30
90.9%
3 1
 
3.0%
6 1
 
3.0%
2 1
 
3.0%

Most occurring scripts

ValueCountFrequency (%)
Common 33
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 30
90.9%
3 1
 
3.0%
6 1
 
3.0%
2 1
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 33
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 30
90.9%
3 1
 
3.0%
6 1
 
3.0%
2 1
 
3.0%

q16_c16_r4
Text

MISSING 

Distinct5
Distinct (%)16.1%
Missing969
Missing (%)96.9%
Memory size32.2 KiB
2023-12-09T22:15:06.651243image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.129032258
Min length1

Characters and Unicode

Total characters35
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)9.7%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 26
83.9%
20 2
 
6.5%
18 1
 
3.2%
3 1
 
3.2%
35 1
 
3.2%
2023-12-09T22:15:06.892097image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 28
80.0%
2 2
 
5.7%
3 2
 
5.7%
1 1
 
2.9%
8 1
 
2.9%
5 1
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 35
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 28
80.0%
2 2
 
5.7%
3 2
 
5.7%
1 1
 
2.9%
8 1
 
2.9%
5 1
 
2.9%

Most occurring scripts

ValueCountFrequency (%)
Common 35
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 28
80.0%
2 2
 
5.7%
3 2
 
5.7%
1 1
 
2.9%
8 1
 
2.9%
5 1
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 35
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 28
80.0%
2 2
 
5.7%
3 2
 
5.7%
1 1
 
2.9%
8 1
 
2.9%
5 1
 
2.9%

q16_c17_r1
Text

MISSING 

Distinct4
Distinct (%)14.8%
Missing973
Missing (%)97.3%
Memory size32.1 KiB
2023-12-09T22:15:07.010446image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.111111111
Min length1

Characters and Unicode

Total characters30
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)11.1%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 24
88.9%
12 1
 
3.7%
20 1
 
3.7%
46 1
 
3.7%
2023-12-09T22:15:07.254443image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 25
83.3%
2 2
 
6.7%
1 1
 
3.3%
4 1
 
3.3%
6 1
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 30
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 25
83.3%
2 2
 
6.7%
1 1
 
3.3%
4 1
 
3.3%
6 1
 
3.3%

Most occurring scripts

ValueCountFrequency (%)
Common 30
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 25
83.3%
2 2
 
6.7%
1 1
 
3.3%
4 1
 
3.3%
6 1
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 30
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 25
83.3%
2 2
 
6.7%
1 1
 
3.3%
4 1
 
3.3%
6 1
 
3.3%

q16_c17_r2
Text

MISSING 

Distinct6
Distinct (%)22.2%
Missing973
Missing (%)97.3%
Memory size32.1 KiB
2023-12-09T22:15:07.377331image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.148148148
Min length1

Characters and Unicode

Total characters31
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)18.5%

Sample

1st row0
2nd row1
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 22
81.5%
12 1
 
3.7%
20 1
 
3.7%
10 1
 
3.7%
1 1
 
3.7%
35 1
 
3.7%
2023-12-09T22:15:07.621518image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 24
77.4%
1 3
 
9.7%
2 2
 
6.5%
3 1
 
3.2%
5 1
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 31
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 24
77.4%
1 3
 
9.7%
2 2
 
6.5%
3 1
 
3.2%
5 1
 
3.2%

Most occurring scripts

ValueCountFrequency (%)
Common 31
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 24
77.4%
1 3
 
9.7%
2 2
 
6.5%
3 1
 
3.2%
5 1
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 31
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 24
77.4%
1 3
 
9.7%
2 2
 
6.5%
3 1
 
3.2%
5 1
 
3.2%

q16_c17_r3
Text

MISSING 

Distinct4
Distinct (%)14.8%
Missing973
Missing (%)97.3%
Memory size32.1 KiB
2023-12-09T22:15:07.735355image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.111111111
Min length1

Characters and Unicode

Total characters30
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)11.1%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 24
88.9%
36 1
 
3.7%
12 1
 
3.7%
20 1
 
3.7%
2023-12-09T22:15:07.972397image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 25
83.3%
2 2
 
6.7%
3 1
 
3.3%
6 1
 
3.3%
1 1
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 30
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 25
83.3%
2 2
 
6.7%
3 1
 
3.3%
6 1
 
3.3%
1 1
 
3.3%

Most occurring scripts

ValueCountFrequency (%)
Common 30
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 25
83.3%
2 2
 
6.7%
3 1
 
3.3%
6 1
 
3.3%
1 1
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 30
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 25
83.3%
2 2
 
6.7%
3 1
 
3.3%
6 1
 
3.3%
1 1
 
3.3%

q16_c17_r4
Text

MISSING 

Distinct6
Distinct (%)22.2%
Missing973
Missing (%)97.3%
Memory size32.1 KiB
2023-12-09T22:15:08.089076image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.185185185
Min length1

Characters and Unicode

Total characters32
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)14.8%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 21
77.8%
20 2
 
7.4%
12 1
 
3.7%
18 1
 
3.7%
3 1
 
3.7%
35 1
 
3.7%
2023-12-09T22:15:08.330205image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 23
71.9%
2 3
 
9.4%
1 2
 
6.2%
3 2
 
6.2%
8 1
 
3.1%
5 1
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 32
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 23
71.9%
2 3
 
9.4%
1 2
 
6.2%
3 2
 
6.2%
8 1
 
3.1%
5 1
 
3.1%

Most occurring scripts

ValueCountFrequency (%)
Common 32
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 23
71.9%
2 3
 
9.4%
1 2
 
6.2%
3 2
 
6.2%
8 1
 
3.1%
5 1
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 32
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 23
71.9%
2 3
 
9.4%
1 2
 
6.2%
3 2
 
6.2%
8 1
 
3.1%
5 1
 
3.1%

q16_c18_r1
Text

MISSING 

Distinct4
Distinct (%)17.4%
Missing977
Missing (%)97.7%
Memory size32.0 KiB
2023-12-09T22:15:08.448814image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.173913043
Min length1

Characters and Unicode

Total characters27
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)8.7%

Sample

1st row0
2nd row0
3rd row0
4th row12
5th row0
ValueCountFrequency (%)
0 19
82.6%
12 2
 
8.7%
20 1
 
4.3%
46 1
 
4.3%
2023-12-09T22:15:08.724766image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 20
74.1%
2 3
 
11.1%
1 2
 
7.4%
4 1
 
3.7%
6 1
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 27
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 20
74.1%
2 3
 
11.1%
1 2
 
7.4%
4 1
 
3.7%
6 1
 
3.7%

Most occurring scripts

ValueCountFrequency (%)
Common 27
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 20
74.1%
2 3
 
11.1%
1 2
 
7.4%
4 1
 
3.7%
6 1
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 27
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 20
74.1%
2 3
 
11.1%
1 2
 
7.4%
4 1
 
3.7%
6 1
 
3.7%

q16_c18_r2
Text

MISSING 

Distinct6
Distinct (%)26.1%
Missing977
Missing (%)97.7%
Memory size32.0 KiB
2023-12-09T22:15:08.850483image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.173913043
Min length1

Characters and Unicode

Total characters27
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)21.7%

Sample

1st row0
2nd row1
3rd row0
4th row10
5th row0
ValueCountFrequency (%)
0 18
78.3%
12 1
 
4.3%
20 1
 
4.3%
10 1
 
4.3%
1 1
 
4.3%
35 1
 
4.3%
2023-12-09T22:15:09.094257image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 20
74.1%
1 3
 
11.1%
2 2
 
7.4%
3 1
 
3.7%
5 1
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 27
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 20
74.1%
1 3
 
11.1%
2 2
 
7.4%
3 1
 
3.7%
5 1
 
3.7%

Most occurring scripts

ValueCountFrequency (%)
Common 27
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 20
74.1%
1 3
 
11.1%
2 2
 
7.4%
3 1
 
3.7%
5 1
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 27
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 20
74.1%
1 3
 
11.1%
2 2
 
7.4%
3 1
 
3.7%
5 1
 
3.7%

q16_c18_r3
Text

MISSING 

Distinct5
Distinct (%)21.7%
Missing977
Missing (%)97.7%
Memory size32.0 KiB
2023-12-09T22:15:09.219664image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.130434783
Min length1

Characters and Unicode

Total characters26
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)17.4%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 19
82.6%
36 1
 
4.3%
12 1
 
4.3%
20 1
 
4.3%
1 1
 
4.3%
2023-12-09T22:15:09.459007image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 20
76.9%
1 2
 
7.7%
2 2
 
7.7%
3 1
 
3.8%
6 1
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 26
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 20
76.9%
1 2
 
7.7%
2 2
 
7.7%
3 1
 
3.8%
6 1
 
3.8%

Most occurring scripts

ValueCountFrequency (%)
Common 26
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 20
76.9%
1 2
 
7.7%
2 2
 
7.7%
3 1
 
3.8%
6 1
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 26
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 20
76.9%
1 2
 
7.7%
2 2
 
7.7%
3 1
 
3.8%
6 1
 
3.8%

q16_c18_r4
Text

MISSING 

Distinct5
Distinct (%)21.7%
Missing977
Missing (%)97.7%
Memory size32.0 KiB
2023-12-09T22:15:09.574902image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.173913043
Min length1

Characters and Unicode

Total characters27
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)17.4%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 19
82.6%
12 1
 
4.3%
20 1
 
4.3%
18 1
 
4.3%
35 1
 
4.3%
2023-12-09T22:15:09.821034image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 20
74.1%
1 2
 
7.4%
2 2
 
7.4%
8 1
 
3.7%
3 1
 
3.7%
5 1
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 27
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 20
74.1%
1 2
 
7.4%
2 2
 
7.4%
8 1
 
3.7%
3 1
 
3.7%
5 1
 
3.7%

Most occurring scripts

ValueCountFrequency (%)
Common 27
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 20
74.1%
1 2
 
7.4%
2 2
 
7.4%
8 1
 
3.7%
3 1
 
3.7%
5 1
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 27
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 20
74.1%
1 2
 
7.4%
2 2
 
7.4%
8 1
 
3.7%
3 1
 
3.7%
5 1
 
3.7%

q16_c19_r1
Text

MISSING 

Distinct4
Distinct (%)18.2%
Missing978
Missing (%)97.8%
Memory size31.9 KiB
2023-12-09T22:15:09.938984image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.181818182
Min length1

Characters and Unicode

Total characters26
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)9.1%

Sample

1st row0
2nd row0
3rd row0
4th row12
5th row0
ValueCountFrequency (%)
0 18
81.8%
12 2
 
9.1%
20 1
 
4.5%
46 1
 
4.5%
2023-12-09T22:15:10.189541image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 19
73.1%
2 3
 
11.5%
1 2
 
7.7%
4 1
 
3.8%
6 1
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 26
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 19
73.1%
2 3
 
11.5%
1 2
 
7.7%
4 1
 
3.8%
6 1
 
3.8%

Most occurring scripts

ValueCountFrequency (%)
Common 26
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 19
73.1%
2 3
 
11.5%
1 2
 
7.7%
4 1
 
3.8%
6 1
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 26
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 19
73.1%
2 3
 
11.5%
1 2
 
7.7%
4 1
 
3.8%
6 1
 
3.8%

q16_c19_r2
Text

MISSING 

Distinct5
Distinct (%)22.7%
Missing978
Missing (%)97.8%
Memory size31.9 KiB
2023-12-09T22:15:10.312365image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.136363636
Min length1

Characters and Unicode

Total characters25
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)18.2%

Sample

1st row0
2nd row1
3rd row0
4th row10
5th row0
ValueCountFrequency (%)
0 18
81.8%
12 1
 
4.5%
20 1
 
4.5%
10 1
 
4.5%
1 1
 
4.5%
2023-12-09T22:15:10.560230image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 20
80.0%
1 3
 
12.0%
2 2
 
8.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 25
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 20
80.0%
1 3
 
12.0%
2 2
 
8.0%

Most occurring scripts

ValueCountFrequency (%)
Common 25
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 20
80.0%
1 3
 
12.0%
2 2
 
8.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 25
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 20
80.0%
1 3
 
12.0%
2 2
 
8.0%

q16_c19_r3
Text

MISSING 

Distinct4
Distinct (%)18.2%
Missing978
Missing (%)97.8%
Memory size31.9 KiB
2023-12-09T22:15:10.674577image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.136363636
Min length1

Characters and Unicode

Total characters25
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)13.6%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 19
86.4%
36 1
 
4.5%
12 1
 
4.5%
20 1
 
4.5%
2023-12-09T22:15:10.916189image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 20
80.0%
2 2
 
8.0%
3 1
 
4.0%
6 1
 
4.0%
1 1
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 25
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 20
80.0%
2 2
 
8.0%
3 1
 
4.0%
6 1
 
4.0%
1 1
 
4.0%

Most occurring scripts

ValueCountFrequency (%)
Common 25
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 20
80.0%
2 2
 
8.0%
3 1
 
4.0%
6 1
 
4.0%
1 1
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 25
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 20
80.0%
2 2
 
8.0%
3 1
 
4.0%
6 1
 
4.0%
1 1
 
4.0%

q16_c19_r4
Text

MISSING 

Distinct4
Distinct (%)18.2%
Missing978
Missing (%)97.8%
Memory size31.9 KiB
2023-12-09T22:15:11.030737image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.136363636
Min length1

Characters and Unicode

Total characters25
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)13.6%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 19
86.4%
12 1
 
4.5%
20 1
 
4.5%
18 1
 
4.5%
2023-12-09T22:15:11.280167image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 20
80.0%
1 2
 
8.0%
2 2
 
8.0%
8 1
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 25
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 20
80.0%
1 2
 
8.0%
2 2
 
8.0%
8 1
 
4.0%

Most occurring scripts

ValueCountFrequency (%)
Common 25
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 20
80.0%
1 2
 
8.0%
2 2
 
8.0%
8 1
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 25
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 20
80.0%
1 2
 
8.0%
2 2
 
8.0%
8 1
 
4.0%

q16_c20_r1
Text

MISSING 

Distinct4
Distinct (%)20.0%
Missing980
Missing (%)98.0%
Memory size31.9 KiB
2023-12-09T22:15:11.395860image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.15
Min length1

Characters and Unicode

Total characters23
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)15.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 17
85.0%
12 1
 
5.0%
20 1
 
5.0%
46 1
 
5.0%
2023-12-09T22:15:11.653644image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 18
78.3%
2 2
 
8.7%
1 1
 
4.3%
4 1
 
4.3%
6 1
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 23
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 18
78.3%
2 2
 
8.7%
1 1
 
4.3%
4 1
 
4.3%
6 1
 
4.3%

Most occurring scripts

ValueCountFrequency (%)
Common 23
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 18
78.3%
2 2
 
8.7%
1 1
 
4.3%
4 1
 
4.3%
6 1
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 23
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 18
78.3%
2 2
 
8.7%
1 1
 
4.3%
4 1
 
4.3%
6 1
 
4.3%

q16_c20_r2
Text

MISSING 

Distinct5
Distinct (%)25.0%
Missing980
Missing (%)98.0%
Memory size31.9 KiB
2023-12-09T22:15:11.772775image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.15
Min length1

Characters and Unicode

Total characters23
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)20.0%

Sample

1st row0
2nd row1
3rd row0
4th row10
5th row0
ValueCountFrequency (%)
0 16
80.0%
12 1
 
5.0%
20 1
 
5.0%
10 1
 
5.0%
1 1
 
5.0%
2023-12-09T22:15:12.026350image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 18
78.3%
1 3
 
13.0%
2 2
 
8.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 23
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 18
78.3%
1 3
 
13.0%
2 2
 
8.7%

Most occurring scripts

ValueCountFrequency (%)
Common 23
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 18
78.3%
1 3
 
13.0%
2 2
 
8.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 23
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 18
78.3%
1 3
 
13.0%
2 2
 
8.7%

q16_c20_r3
Text

MISSING 

Distinct4
Distinct (%)20.0%
Missing980
Missing (%)98.0%
Memory size31.9 KiB
2023-12-09T22:15:12.145041image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.15
Min length1

Characters and Unicode

Total characters23
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)15.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 17
85.0%
36 1
 
5.0%
12 1
 
5.0%
20 1
 
5.0%
2023-12-09T22:15:12.386580image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 18
78.3%
2 2
 
8.7%
3 1
 
4.3%
6 1
 
4.3%
1 1
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 23
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 18
78.3%
2 2
 
8.7%
3 1
 
4.3%
6 1
 
4.3%
1 1
 
4.3%

Most occurring scripts

ValueCountFrequency (%)
Common 23
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 18
78.3%
2 2
 
8.7%
3 1
 
4.3%
6 1
 
4.3%
1 1
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 23
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 18
78.3%
2 2
 
8.7%
3 1
 
4.3%
6 1
 
4.3%
1 1
 
4.3%

q16_c20_r4
Text

MISSING 

Distinct4
Distinct (%)20.0%
Missing980
Missing (%)98.0%
Memory size31.9 KiB
2023-12-09T22:15:12.501712image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.2
Min length1

Characters and Unicode

Total characters24
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)10.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row20
ValueCountFrequency (%)
0 16
80.0%
20 2
 
10.0%
12 1
 
5.0%
18 1
 
5.0%
2023-12-09T22:15:12.735467image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 18
75.0%
2 3
 
12.5%
1 2
 
8.3%
8 1
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 24
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 18
75.0%
2 3
 
12.5%
1 2
 
8.3%
8 1
 
4.2%

Most occurring scripts

ValueCountFrequency (%)
Common 24
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 18
75.0%
2 3
 
12.5%
1 2
 
8.3%
8 1
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 18
75.0%
2 3
 
12.5%
1 2
 
8.3%
8 1
 
4.2%

q16_c21_r1
Text

MISSING 

Distinct4
Distinct (%)23.5%
Missing983
Missing (%)98.3%
Memory size31.8 KiB
2023-12-09T22:15:12.848898image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.235294118
Min length1

Characters and Unicode

Total characters21
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)11.8%

Sample

1st row0
2nd row0
3rd row12
4th row20
5th row0
ValueCountFrequency (%)
0 13
76.5%
12 2
 
11.8%
20 1
 
5.9%
46 1
 
5.9%
2023-12-09T22:15:13.083775image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 14
66.7%
2 3
 
14.3%
1 2
 
9.5%
4 1
 
4.8%
6 1
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 21
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 14
66.7%
2 3
 
14.3%
1 2
 
9.5%
4 1
 
4.8%
6 1
 
4.8%

Most occurring scripts

ValueCountFrequency (%)
Common 21
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 14
66.7%
2 3
 
14.3%
1 2
 
9.5%
4 1
 
4.8%
6 1
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 21
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 14
66.7%
2 3
 
14.3%
1 2
 
9.5%
4 1
 
4.8%
6 1
 
4.8%

q16_c21_r2
Text

MISSING 

Distinct4
Distinct (%)23.5%
Missing983
Missing (%)98.3%
Memory size31.8 KiB
2023-12-09T22:15:13.201021image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.176470588
Min length1

Characters and Unicode

Total characters20
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)17.6%

Sample

1st row0
2nd row0
3rd row10
4th row20
5th row0
ValueCountFrequency (%)
0 14
82.4%
12 1
 
5.9%
20 1
 
5.9%
10 1
 
5.9%
2023-12-09T22:15:13.447452image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 16
80.0%
1 2
 
10.0%
2 2
 
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 20
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 16
80.0%
1 2
 
10.0%
2 2
 
10.0%

Most occurring scripts

ValueCountFrequency (%)
Common 20
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 16
80.0%
1 2
 
10.0%
2 2
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 20
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 16
80.0%
1 2
 
10.0%
2 2
 
10.0%

q16_c21_r3
Text

MISSING 

Distinct4
Distinct (%)23.5%
Missing983
Missing (%)98.3%
Memory size31.8 KiB
2023-12-09T22:15:13.566454image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.176470588
Min length1

Characters and Unicode

Total characters20
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)17.6%

Sample

1st row0
2nd row0
3rd row0
4th row20
5th row0
ValueCountFrequency (%)
0 14
82.4%
36 1
 
5.9%
12 1
 
5.9%
20 1
 
5.9%
2023-12-09T22:15:13.805149image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 15
75.0%
2 2
 
10.0%
3 1
 
5.0%
6 1
 
5.0%
1 1
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 20
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 15
75.0%
2 2
 
10.0%
3 1
 
5.0%
6 1
 
5.0%
1 1
 
5.0%

Most occurring scripts

ValueCountFrequency (%)
Common 20
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 15
75.0%
2 2
 
10.0%
3 1
 
5.0%
6 1
 
5.0%
1 1
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 20
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 15
75.0%
2 2
 
10.0%
3 1
 
5.0%
6 1
 
5.0%
1 1
 
5.0%

q16_c21_r4
Text

MISSING 

Distinct4
Distinct (%)23.5%
Missing983
Missing (%)98.3%
Memory size31.8 KiB
2023-12-09T22:15:13.919541image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.176470588
Min length1

Characters and Unicode

Total characters20
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)17.6%

Sample

1st row0
2nd row0
3rd row0
4th row20
5th row0
ValueCountFrequency (%)
0 14
82.4%
12 1
 
5.9%
20 1
 
5.9%
18 1
 
5.9%
2023-12-09T22:15:14.157660image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 15
75.0%
1 2
 
10.0%
2 2
 
10.0%
8 1
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 20
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 15
75.0%
1 2
 
10.0%
2 2
 
10.0%
8 1
 
5.0%

Most occurring scripts

ValueCountFrequency (%)
Common 20
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 15
75.0%
1 2
 
10.0%
2 2
 
10.0%
8 1
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 20
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 15
75.0%
1 2
 
10.0%
2 2
 
10.0%
8 1
 
5.0%

q16_c22_r1
Text

MISSING 

Distinct4
Distinct (%)28.6%
Missing986
Missing (%)98.6%
Memory size31.7 KiB
2023-12-09T22:15:14.270843image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.214285714
Min length1

Characters and Unicode

Total characters17
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)21.4%

Sample

1st row0
2nd row0
3rd row12
4th row20
5th row0
ValueCountFrequency (%)
0 11
78.6%
12 1
 
7.1%
20 1
 
7.1%
46 1
 
7.1%
2023-12-09T22:15:14.503034image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12
70.6%
2 2
 
11.8%
1 1
 
5.9%
4 1
 
5.9%
6 1
 
5.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 17
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 12
70.6%
2 2
 
11.8%
1 1
 
5.9%
4 1
 
5.9%
6 1
 
5.9%

Most occurring scripts

ValueCountFrequency (%)
Common 17
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 12
70.6%
2 2
 
11.8%
1 1
 
5.9%
4 1
 
5.9%
6 1
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 12
70.6%
2 2
 
11.8%
1 1
 
5.9%
4 1
 
5.9%
6 1
 
5.9%

q16_c22_r2
Text

MISSING 

Distinct4
Distinct (%)28.6%
Missing986
Missing (%)98.6%
Memory size31.7 KiB
2023-12-09T22:15:14.616063image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.214285714
Min length1

Characters and Unicode

Total characters17
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)21.4%

Sample

1st row0
2nd row0
3rd row10
4th row20
5th row0
ValueCountFrequency (%)
0 11
78.6%
20 1
 
7.1%
10 1
 
7.1%
35 1
 
7.1%
2023-12-09T22:15:14.846562image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13
76.5%
2 1
 
5.9%
1 1
 
5.9%
3 1
 
5.9%
5 1
 
5.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 17
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 13
76.5%
2 1
 
5.9%
1 1
 
5.9%
3 1
 
5.9%
5 1
 
5.9%

Most occurring scripts

ValueCountFrequency (%)
Common 17
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 13
76.5%
2 1
 
5.9%
1 1
 
5.9%
3 1
 
5.9%
5 1
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 13
76.5%
2 1
 
5.9%
1 1
 
5.9%
3 1
 
5.9%
5 1
 
5.9%

q16_c22_r3
Text

MISSING 

Distinct4
Distinct (%)28.6%
Missing986
Missing (%)98.6%
Memory size31.7 KiB
2023-12-09T22:15:14.958696image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.142857143
Min length1

Characters and Unicode

Total characters16
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)21.4%

Sample

1st row0
2nd row0
3rd row0
4th row20
5th row0
ValueCountFrequency (%)
0 11
78.6%
36 1
 
7.1%
20 1
 
7.1%
1 1
 
7.1%
2023-12-09T22:15:15.199005image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12
75.0%
3 1
 
6.2%
6 1
 
6.2%
2 1
 
6.2%
1 1
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 16
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 12
75.0%
3 1
 
6.2%
6 1
 
6.2%
2 1
 
6.2%
1 1
 
6.2%

Most occurring scripts

ValueCountFrequency (%)
Common 16
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 12
75.0%
3 1
 
6.2%
6 1
 
6.2%
2 1
 
6.2%
1 1
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 12
75.0%
3 1
 
6.2%
6 1
 
6.2%
2 1
 
6.2%
1 1
 
6.2%

q16_c22_r4
Text

MISSING 

Distinct3
Distinct (%)21.4%
Missing986
Missing (%)98.6%
Memory size31.7 KiB
2023-12-09T22:15:15.310223image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.142857143
Min length1

Characters and Unicode

Total characters16
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)14.3%

Sample

1st row0
2nd row0
3rd row0
4th row20
5th row0
ValueCountFrequency (%)
0 12
85.7%
20 1
 
7.1%
18 1
 
7.1%
2023-12-09T22:15:16.121612image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13
81.2%
2 1
 
6.2%
1 1
 
6.2%
8 1
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 16
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 13
81.2%
2 1
 
6.2%
1 1
 
6.2%
8 1
 
6.2%

Most occurring scripts

ValueCountFrequency (%)
Common 16
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 13
81.2%
2 1
 
6.2%
1 1
 
6.2%
8 1
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 13
81.2%
2 1
 
6.2%
1 1
 
6.2%
8 1
 
6.2%

q16_c23_r1
Text

MISSING 

Distinct4
Distinct (%)36.4%
Missing989
Missing (%)98.9%
Memory size31.7 KiB
2023-12-09T22:15:16.238128image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.272727273
Min length1

Characters and Unicode

Total characters14
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)27.3%

Sample

1st row0
2nd row0
3rd row20
4th row0
5th row0
ValueCountFrequency (%)
0 8
72.7%
12 1
 
9.1%
20 1
 
9.1%
46 1
 
9.1%
2023-12-09T22:15:16.472600image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9
64.3%
2 2
 
14.3%
1 1
 
7.1%
4 1
 
7.1%
6 1
 
7.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 14
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9
64.3%
2 2
 
14.3%
1 1
 
7.1%
4 1
 
7.1%
6 1
 
7.1%

Most occurring scripts

ValueCountFrequency (%)
Common 14
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 9
64.3%
2 2
 
14.3%
1 1
 
7.1%
4 1
 
7.1%
6 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 9
64.3%
2 2
 
14.3%
1 1
 
7.1%
4 1
 
7.1%
6 1
 
7.1%

q16_c23_r2
Text

MISSING 

Distinct4
Distinct (%)36.4%
Missing989
Missing (%)98.9%
Memory size31.7 KiB
2023-12-09T22:15:16.588371image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.272727273
Min length1

Characters and Unicode

Total characters14
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)27.3%

Sample

1st row0
2nd row0
3rd row20
4th row0
5th row0
ValueCountFrequency (%)
0 8
72.7%
12 1
 
9.1%
20 1
 
9.1%
35 1
 
9.1%
2023-12-09T22:15:16.823816image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9
64.3%
2 2
 
14.3%
1 1
 
7.1%
3 1
 
7.1%
5 1
 
7.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 14
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9
64.3%
2 2
 
14.3%
1 1
 
7.1%
3 1
 
7.1%
5 1
 
7.1%

Most occurring scripts

ValueCountFrequency (%)
Common 14
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 9
64.3%
2 2
 
14.3%
1 1
 
7.1%
3 1
 
7.1%
5 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 9
64.3%
2 2
 
14.3%
1 1
 
7.1%
3 1
 
7.1%
5 1
 
7.1%

q16_c23_r3
Text

MISSING 

Distinct5
Distinct (%)45.5%
Missing989
Missing (%)98.9%
Memory size31.7 KiB
2023-12-09T22:15:16.948555image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.272727273
Min length1

Characters and Unicode

Total characters14
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)36.4%

Sample

1st row0
2nd row0
3rd row20
4th row0
5th row0
ValueCountFrequency (%)
0 7
63.6%
36 1
 
9.1%
12 1
 
9.1%
20 1
 
9.1%
1 1
 
9.1%
2023-12-09T22:15:17.192305image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 8
57.1%
1 2
 
14.3%
2 2
 
14.3%
3 1
 
7.1%
6 1
 
7.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 14
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 8
57.1%
1 2
 
14.3%
2 2
 
14.3%
3 1
 
7.1%
6 1
 
7.1%

Most occurring scripts

ValueCountFrequency (%)
Common 14
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 8
57.1%
1 2
 
14.3%
2 2
 
14.3%
3 1
 
7.1%
6 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 8
57.1%
1 2
 
14.3%
2 2
 
14.3%
3 1
 
7.1%
6 1
 
7.1%

q16_c23_r4
Text

MISSING 

Distinct4
Distinct (%)36.4%
Missing989
Missing (%)98.9%
Memory size31.7 KiB
2023-12-09T22:15:17.311396image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.272727273
Min length1

Characters and Unicode

Total characters14
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)27.3%

Sample

1st row0
2nd row0
3rd row20
4th row0
5th row0
ValueCountFrequency (%)
0 8
72.7%
12 1
 
9.1%
20 1
 
9.1%
18 1
 
9.1%
2023-12-09T22:15:17.541156image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9
64.3%
1 2
 
14.3%
2 2
 
14.3%
8 1
 
7.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 14
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9
64.3%
1 2
 
14.3%
2 2
 
14.3%
8 1
 
7.1%

Most occurring scripts

ValueCountFrequency (%)
Common 14
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 9
64.3%
1 2
 
14.3%
2 2
 
14.3%
8 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 9
64.3%
1 2
 
14.3%
2 2
 
14.3%
8 1
 
7.1%

q17_c1_r1
Text

MISSING 

Distinct38
Distinct (%)6.9%
Missing452
Missing (%)45.2%
Memory size45.4 KiB
2023-12-09T22:15:17.711100image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.177007299
Min length1

Characters and Unicode

Total characters645
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)2.7%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 391
71.4%
10 24
 
4.4%
1 21
 
3.8%
20 12
 
2.2%
2 11
 
2.0%
5 10
 
1.8%
6 7
 
1.3%
30 7
 
1.3%
15 7
 
1.3%
25 6
 
1.1%
Other values (28) 52
 
9.5%
2023-12-09T22:15:18.017219image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 444
68.8%
1 74
 
11.5%
2 41
 
6.4%
5 27
 
4.2%
3 17
 
2.6%
6 13
 
2.0%
8 11
 
1.7%
7 9
 
1.4%
4 7
 
1.1%
9 2
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 645
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 444
68.8%
1 74
 
11.5%
2 41
 
6.4%
5 27
 
4.2%
3 17
 
2.6%
6 13
 
2.0%
8 11
 
1.7%
7 9
 
1.4%
4 7
 
1.1%
9 2
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
Common 645
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 444
68.8%
1 74
 
11.5%
2 41
 
6.4%
5 27
 
4.2%
3 17
 
2.6%
6 13
 
2.0%
8 11
 
1.7%
7 9
 
1.4%
4 7
 
1.1%
9 2
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 645
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 444
68.8%
1 74
 
11.5%
2 41
 
6.4%
5 27
 
4.2%
3 17
 
2.6%
6 13
 
2.0%
8 11
 
1.7%
7 9
 
1.4%
4 7
 
1.1%
9 2
 
0.3%

q17_c1_r2
Text

MISSING 

Distinct48
Distinct (%)8.8%
Missing452
Missing (%)45.2%
Memory size45.4 KiB
2023-12-09T22:15:18.216121image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length4
Median length1
Mean length1.22080292
Min length1

Characters and Unicode

Total characters669
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)3.6%

Sample

1st row30
2nd row0
3rd row35
4th row0
5th row0
ValueCountFrequency (%)
0 380
69.3%
1 22
 
4.0%
5 15
 
2.7%
10 14
 
2.6%
20 12
 
2.2%
30 10
 
1.8%
2 9
 
1.6%
40 7
 
1.3%
50 6
 
1.1%
12 5
 
0.9%
Other values (38) 68
 
12.4%
2023-12-09T22:15:18.543848image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 445
66.5%
1 67
 
10.0%
2 46
 
6.9%
5 41
 
6.1%
3 27
 
4.0%
4 18
 
2.7%
6 9
 
1.3%
7 7
 
1.0%
8 6
 
0.9%
9 3
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 669
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 445
66.5%
1 67
 
10.0%
2 46
 
6.9%
5 41
 
6.1%
3 27
 
4.0%
4 18
 
2.7%
6 9
 
1.3%
7 7
 
1.0%
8 6
 
0.9%
9 3
 
0.4%

Most occurring scripts

ValueCountFrequency (%)
Common 669
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 445
66.5%
1 67
 
10.0%
2 46
 
6.9%
5 41
 
6.1%
3 27
 
4.0%
4 18
 
2.7%
6 9
 
1.3%
7 7
 
1.0%
8 6
 
0.9%
9 3
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 669
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 445
66.5%
1 67
 
10.0%
2 46
 
6.9%
5 41
 
6.1%
3 27
 
4.0%
4 18
 
2.7%
6 9
 
1.3%
7 7
 
1.0%
8 6
 
0.9%
9 3
 
0.4%

q17_c1_r3
Text

MISSING 

Distinct29
Distinct (%)5.3%
Missing452
Missing (%)45.2%
Memory size45.4 KiB
2023-12-09T22:15:18.705803image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.122262774
Min length1

Characters and Unicode

Total characters615
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)2.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row8
ValueCountFrequency (%)
0 433
79.0%
10 16
 
2.9%
5 15
 
2.7%
1 14
 
2.6%
15 7
 
1.3%
2 7
 
1.3%
30 7
 
1.3%
20 7
 
1.3%
8 7
 
1.3%
25 4
 
0.7%
Other values (19) 31
 
5.7%
2023-12-09T22:15:19.009549image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 470
76.4%
1 52
 
8.5%
5 31
 
5.0%
2 25
 
4.1%
3 11
 
1.8%
8 10
 
1.6%
4 6
 
1.0%
7 4
 
0.7%
6 4
 
0.7%
9 2
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 615
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 470
76.4%
1 52
 
8.5%
5 31
 
5.0%
2 25
 
4.1%
3 11
 
1.8%
8 10
 
1.6%
4 6
 
1.0%
7 4
 
0.7%
6 4
 
0.7%
9 2
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
Common 615
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 470
76.4%
1 52
 
8.5%
5 31
 
5.0%
2 25
 
4.1%
3 11
 
1.8%
8 10
 
1.6%
4 6
 
1.0%
7 4
 
0.7%
6 4
 
0.7%
9 2
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 615
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 470
76.4%
1 52
 
8.5%
5 31
 
5.0%
2 25
 
4.1%
3 11
 
1.8%
8 10
 
1.6%
4 6
 
1.0%
7 4
 
0.7%
6 4
 
0.7%
9 2
 
0.3%

q17_c1_r4
Text

MISSING 

Distinct43
Distinct (%)7.8%
Missing452
Missing (%)45.2%
Memory size45.4 KiB
2023-12-09T22:15:19.200348image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.222627737
Min length1

Characters and Unicode

Total characters670
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)2.6%

Sample

1st row0
2nd row30
3rd row35
4th row0
5th row0
ValueCountFrequency (%)
0 381
69.5%
20 15
 
2.7%
10 15
 
2.7%
1 15
 
2.7%
30 11
 
2.0%
40 10
 
1.8%
2 10
 
1.8%
5 9
 
1.6%
50 6
 
1.1%
8 6
 
1.1%
Other values (33) 70
 
12.8%
2023-12-09T22:15:19.531780image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 454
67.8%
1 62
 
9.3%
2 40
 
6.0%
5 31
 
4.6%
3 25
 
3.7%
4 21
 
3.1%
8 15
 
2.2%
6 10
 
1.5%
9 6
 
0.9%
7 6
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 670
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 454
67.8%
1 62
 
9.3%
2 40
 
6.0%
5 31
 
4.6%
3 25
 
3.7%
4 21
 
3.1%
8 15
 
2.2%
6 10
 
1.5%
9 6
 
0.9%
7 6
 
0.9%

Most occurring scripts

ValueCountFrequency (%)
Common 670
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 454
67.8%
1 62
 
9.3%
2 40
 
6.0%
5 31
 
4.6%
3 25
 
3.7%
4 21
 
3.1%
8 15
 
2.2%
6 10
 
1.5%
9 6
 
0.9%
7 6
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 670
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 454
67.8%
1 62
 
9.3%
2 40
 
6.0%
5 31
 
4.6%
3 25
 
3.7%
4 21
 
3.1%
8 15
 
2.2%
6 10
 
1.5%
9 6
 
0.9%
7 6
 
0.9%

q17_c2_r1
Text

MISSING 

Distinct39
Distinct (%)7.2%
Missing455
Missing (%)45.5%
Memory size45.3 KiB
2023-12-09T22:15:19.705761image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.179816514
Min length1

Characters and Unicode

Total characters643
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)2.9%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 386
70.8%
10 24
 
4.4%
1 21
 
3.9%
5 12
 
2.2%
20 12
 
2.2%
2 10
 
1.8%
6 9
 
1.7%
30 7
 
1.3%
15 6
 
1.1%
12 6
 
1.1%
Other values (29) 52
 
9.5%
2023-12-09T22:15:20.011524image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 439
68.3%
1 72
 
11.2%
2 41
 
6.4%
5 29
 
4.5%
3 19
 
3.0%
6 16
 
2.5%
8 10
 
1.6%
7 8
 
1.2%
4 7
 
1.1%
9 2
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 643
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 439
68.3%
1 72
 
11.2%
2 41
 
6.4%
5 29
 
4.5%
3 19
 
3.0%
6 16
 
2.5%
8 10
 
1.6%
7 8
 
1.2%
4 7
 
1.1%
9 2
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
Common 643
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 439
68.3%
1 72
 
11.2%
2 41
 
6.4%
5 29
 
4.5%
3 19
 
3.0%
6 16
 
2.5%
8 10
 
1.6%
7 8
 
1.2%
4 7
 
1.1%
9 2
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 643
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 439
68.3%
1 72
 
11.2%
2 41
 
6.4%
5 29
 
4.5%
3 19
 
3.0%
6 16
 
2.5%
8 10
 
1.6%
7 8
 
1.2%
4 7
 
1.1%
9 2
 
0.3%

q17_c2_r2
Text

MISSING 

Distinct47
Distinct (%)8.6%
Missing455
Missing (%)45.5%
Memory size45.3 KiB
2023-12-09T22:15:20.200117image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length4
Median length1
Mean length1.220183486
Min length1

Characters and Unicode

Total characters665
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)3.7%

Sample

1st row30
2nd row0
3rd row35
4th row0
5th row0
ValueCountFrequency (%)
0 373
68.4%
1 21
 
3.9%
5 17
 
3.1%
10 14
 
2.6%
20 13
 
2.4%
30 10
 
1.8%
40 9
 
1.7%
2 9
 
1.7%
50 7
 
1.3%
12 5
 
0.9%
Other values (37) 67
 
12.3%
2023-12-09T22:15:20.518758image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 440
66.2%
1 63
 
9.5%
2 47
 
7.1%
5 43
 
6.5%
3 27
 
4.1%
4 19
 
2.9%
6 10
 
1.5%
7 7
 
1.1%
8 6
 
0.9%
9 3
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 665
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 440
66.2%
1 63
 
9.5%
2 47
 
7.1%
5 43
 
6.5%
3 27
 
4.1%
4 19
 
2.9%
6 10
 
1.5%
7 7
 
1.1%
8 6
 
0.9%
9 3
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
Common 665
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 440
66.2%
1 63
 
9.5%
2 47
 
7.1%
5 43
 
6.5%
3 27
 
4.1%
4 19
 
2.9%
6 10
 
1.5%
7 7
 
1.1%
8 6
 
0.9%
9 3
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 665
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 440
66.2%
1 63
 
9.5%
2 47
 
7.1%
5 43
 
6.5%
3 27
 
4.1%
4 19
 
2.9%
6 10
 
1.5%
7 7
 
1.1%
8 6
 
0.9%
9 3
 
0.5%

q17_c2_r3
Text

MISSING 

Distinct27
Distinct (%)5.0%
Missing455
Missing (%)45.5%
Memory size45.3 KiB
2023-12-09T22:15:20.677738image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.124770642
Min length1

Characters and Unicode

Total characters613
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)1.7%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row10
ValueCountFrequency (%)
0 428
78.5%
5 17
 
3.1%
10 17
 
3.1%
1 14
 
2.6%
30 8
 
1.5%
15 7
 
1.3%
20 7
 
1.3%
2 6
 
1.1%
8 6
 
1.1%
12 5
 
0.9%
Other values (17) 30
 
5.5%
2023-12-09T22:15:20.974980image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 467
76.2%
1 53
 
8.6%
5 32
 
5.2%
2 24
 
3.9%
3 13
 
2.1%
8 8
 
1.3%
6 6
 
1.0%
4 5
 
0.8%
7 4
 
0.7%
9 1
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 613
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 467
76.2%
1 53
 
8.6%
5 32
 
5.2%
2 24
 
3.9%
3 13
 
2.1%
8 8
 
1.3%
6 6
 
1.0%
4 5
 
0.8%
7 4
 
0.7%
9 1
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Common 613
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 467
76.2%
1 53
 
8.6%
5 32
 
5.2%
2 24
 
3.9%
3 13
 
2.1%
8 8
 
1.3%
6 6
 
1.0%
4 5
 
0.8%
7 4
 
0.7%
9 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 613
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 467
76.2%
1 53
 
8.6%
5 32
 
5.2%
2 24
 
3.9%
3 13
 
2.1%
8 8
 
1.3%
6 6
 
1.0%
4 5
 
0.8%
7 4
 
0.7%
9 1
 
0.2%

q17_c2_r4
Text

MISSING 

Distinct43
Distinct (%)7.9%
Missing455
Missing (%)45.5%
Memory size45.3 KiB
2023-12-09T22:15:21.163837image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.222018349
Min length1

Characters and Unicode

Total characters666
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)2.9%

Sample

1st row0
2nd row30
3rd row35
4th row0
5th row0
ValueCountFrequency (%)
0 380
69.7%
10 15
 
2.8%
1 14
 
2.6%
20 14
 
2.6%
30 12
 
2.2%
40 10
 
1.8%
5 10
 
1.8%
2 10
 
1.8%
8 6
 
1.1%
50 6
 
1.1%
Other values (33) 68
 
12.5%
2023-12-09T22:15:21.492703image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 453
68.0%
1 59
 
8.9%
2 39
 
5.9%
5 32
 
4.8%
3 27
 
4.1%
4 21
 
3.2%
8 15
 
2.3%
6 9
 
1.4%
7 6
 
0.9%
9 5
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 666
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 453
68.0%
1 59
 
8.9%
2 39
 
5.9%
5 32
 
4.8%
3 27
 
4.1%
4 21
 
3.2%
8 15
 
2.3%
6 9
 
1.4%
7 6
 
0.9%
9 5
 
0.8%

Most occurring scripts

ValueCountFrequency (%)
Common 666
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 453
68.0%
1 59
 
8.9%
2 39
 
5.9%
5 32
 
4.8%
3 27
 
4.1%
4 21
 
3.2%
8 15
 
2.3%
6 9
 
1.4%
7 6
 
0.9%
9 5
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 666
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 453
68.0%
1 59
 
8.9%
2 39
 
5.9%
5 32
 
4.8%
3 27
 
4.1%
4 21
 
3.2%
8 15
 
2.3%
6 9
 
1.4%
7 6
 
0.9%
9 5
 
0.8%

q17_c3_r1
Text

MISSING 

Distinct37
Distinct (%)6.9%
Missing465
Missing (%)46.5%
Memory size45.0 KiB
2023-12-09T22:15:21.672807image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.173831776
Min length1

Characters and Unicode

Total characters628
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)2.8%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 377
70.5%
10 22
 
4.1%
1 21
 
3.9%
5 12
 
2.2%
20 12
 
2.2%
2 11
 
2.1%
8 8
 
1.5%
6 8
 
1.5%
30 7
 
1.3%
25 6
 
1.1%
Other values (27) 51
 
9.5%
2023-12-09T22:15:22.005442image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 427
68.0%
1 69
 
11.0%
2 42
 
6.7%
5 29
 
4.6%
3 16
 
2.5%
6 15
 
2.4%
8 12
 
1.9%
7 9
 
1.4%
4 7
 
1.1%
9 2
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 628
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 427
68.0%
1 69
 
11.0%
2 42
 
6.7%
5 29
 
4.6%
3 16
 
2.5%
6 15
 
2.4%
8 12
 
1.9%
7 9
 
1.4%
4 7
 
1.1%
9 2
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
Common 628
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 427
68.0%
1 69
 
11.0%
2 42
 
6.7%
5 29
 
4.6%
3 16
 
2.5%
6 15
 
2.4%
8 12
 
1.9%
7 9
 
1.4%
4 7
 
1.1%
9 2
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 628
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 427
68.0%
1 69
 
11.0%
2 42
 
6.7%
5 29
 
4.6%
3 16
 
2.5%
6 15
 
2.4%
8 12
 
1.9%
7 9
 
1.4%
4 7
 
1.1%
9 2
 
0.3%

q17_c3_r2
Text

MISSING 

Distinct46
Distinct (%)8.6%
Missing465
Missing (%)46.5%
Memory size45.1 KiB
2023-12-09T22:15:22.202393image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.218691589
Min length1

Characters and Unicode

Total characters652
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)3.9%

Sample

1st row30
2nd row0
3rd row35
4th row0
5th row0
ValueCountFrequency (%)
0 368
68.8%
1 20
 
3.7%
5 17
 
3.2%
20 14
 
2.6%
10 13
 
2.4%
30 10
 
1.9%
40 9
 
1.7%
2 9
 
1.7%
50 6
 
1.1%
12 5
 
0.9%
Other values (36) 64
 
12.0%
2023-12-09T22:15:22.540179image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 433
66.4%
1 60
 
9.2%
2 48
 
7.4%
5 41
 
6.3%
3 25
 
3.8%
4 17
 
2.6%
6 9
 
1.4%
8 8
 
1.2%
7 7
 
1.1%
9 4
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 652
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 433
66.4%
1 60
 
9.2%
2 48
 
7.4%
5 41
 
6.3%
3 25
 
3.8%
4 17
 
2.6%
6 9
 
1.4%
8 8
 
1.2%
7 7
 
1.1%
9 4
 
0.6%

Most occurring scripts

ValueCountFrequency (%)
Common 652
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 433
66.4%
1 60
 
9.2%
2 48
 
7.4%
5 41
 
6.3%
3 25
 
3.8%
4 17
 
2.6%
6 9
 
1.4%
8 8
 
1.2%
7 7
 
1.1%
9 4
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 652
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 433
66.4%
1 60
 
9.2%
2 48
 
7.4%
5 41
 
6.3%
3 25
 
3.8%
4 17
 
2.6%
6 9
 
1.4%
8 8
 
1.2%
7 7
 
1.1%
9 4
 
0.6%

q17_c3_r3
Text

MISSING 

Distinct29
Distinct (%)5.4%
Missing465
Missing (%)46.5%
Memory size45.0 KiB
2023-12-09T22:15:22.705092image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.123364486
Min length1

Characters and Unicode

Total characters601
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)1.9%

Sample

1st row0
2nd row0
3rd row0
4th row20
5th row0
ValueCountFrequency (%)
0 418
78.1%
5 16
 
3.0%
10 16
 
3.0%
1 14
 
2.6%
30 8
 
1.5%
8 8
 
1.5%
15 7
 
1.3%
2 7
 
1.3%
20 6
 
1.1%
25 4
 
0.7%
Other values (19) 31
 
5.8%
2023-12-09T22:15:23.005691image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 455
75.7%
1 52
 
8.7%
5 31
 
5.2%
2 22
 
3.7%
3 13
 
2.2%
8 11
 
1.8%
6 6
 
1.0%
4 5
 
0.8%
7 4
 
0.7%
9 2
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 601
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 455
75.7%
1 52
 
8.7%
5 31
 
5.2%
2 22
 
3.7%
3 13
 
2.2%
8 11
 
1.8%
6 6
 
1.0%
4 5
 
0.8%
7 4
 
0.7%
9 2
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
Common 601
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 455
75.7%
1 52
 
8.7%
5 31
 
5.2%
2 22
 
3.7%
3 13
 
2.2%
8 11
 
1.8%
6 6
 
1.0%
4 5
 
0.8%
7 4
 
0.7%
9 2
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 601
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 455
75.7%
1 52
 
8.7%
5 31
 
5.2%
2 22
 
3.7%
3 13
 
2.2%
8 11
 
1.8%
6 6
 
1.0%
4 5
 
0.8%
7 4
 
0.7%
9 2
 
0.3%

q17_c3_r4
Text

MISSING 

Distinct44
Distinct (%)8.2%
Missing465
Missing (%)46.5%
Memory size45.1 KiB
2023-12-09T22:15:23.198249image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.226168224
Min length1

Characters and Unicode

Total characters656
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)3.4%

Sample

1st row0
2nd row30
3rd row35
4th row0
5th row0
ValueCountFrequency (%)
0 366
68.4%
10 17
 
3.2%
20 15
 
2.8%
1 14
 
2.6%
30 11
 
2.1%
40 10
 
1.9%
5 10
 
1.9%
2 10
 
1.9%
50 7
 
1.3%
8 6
 
1.1%
Other values (34) 69
 
12.9%
2023-12-09T22:15:23.526688image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 440
67.1%
1 59
 
9.0%
2 39
 
5.9%
5 33
 
5.0%
3 26
 
4.0%
4 21
 
3.2%
8 16
 
2.4%
6 11
 
1.7%
7 6
 
0.9%
9 5
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 656
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 440
67.1%
1 59
 
9.0%
2 39
 
5.9%
5 33
 
5.0%
3 26
 
4.0%
4 21
 
3.2%
8 16
 
2.4%
6 11
 
1.7%
7 6
 
0.9%
9 5
 
0.8%

Most occurring scripts

ValueCountFrequency (%)
Common 656
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 440
67.1%
1 59
 
9.0%
2 39
 
5.9%
5 33
 
5.0%
3 26
 
4.0%
4 21
 
3.2%
8 16
 
2.4%
6 11
 
1.7%
7 6
 
0.9%
9 5
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 656
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 440
67.1%
1 59
 
9.0%
2 39
 
5.9%
5 33
 
5.0%
3 26
 
4.0%
4 21
 
3.2%
8 16
 
2.4%
6 11
 
1.7%
7 6
 
0.9%
9 5
 
0.8%

q17_c4_r1
Text

MISSING 

Distinct37
Distinct (%)7.4%
Missing500
Missing (%)50.0%
Memory size44.2 KiB
2023-12-09T22:15:23.702341image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.174
Min length1

Characters and Unicode

Total characters587
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)2.8%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 348
69.6%
1 21
 
4.2%
10 19
 
3.8%
5 12
 
2.4%
2 11
 
2.2%
20 10
 
2.0%
6 8
 
1.6%
30 7
 
1.4%
8 7
 
1.4%
15 6
 
1.2%
Other values (27) 51
 
10.2%
2023-12-09T22:15:24.016025image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 394
67.1%
1 65
 
11.1%
2 38
 
6.5%
5 28
 
4.8%
3 18
 
3.1%
6 15
 
2.6%
8 11
 
1.9%
7 10
 
1.7%
4 5
 
0.9%
9 3
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 587
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 394
67.1%
1 65
 
11.1%
2 38
 
6.5%
5 28
 
4.8%
3 18
 
3.1%
6 15
 
2.6%
8 11
 
1.9%
7 10
 
1.7%
4 5
 
0.9%
9 3
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
Common 587
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 394
67.1%
1 65
 
11.1%
2 38
 
6.5%
5 28
 
4.8%
3 18
 
3.1%
6 15
 
2.6%
8 11
 
1.9%
7 10
 
1.7%
4 5
 
0.9%
9 3
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 587
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 394
67.1%
1 65
 
11.1%
2 38
 
6.5%
5 28
 
4.8%
3 18
 
3.1%
6 15
 
2.6%
8 11
 
1.9%
7 10
 
1.7%
4 5
 
0.9%
9 3
 
0.5%

q17_c4_r2
Text

MISSING 

Distinct46
Distinct (%)9.2%
Missing500
Missing (%)50.0%
Memory size44.2 KiB
2023-12-09T22:15:24.204695image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.208
Min length1

Characters and Unicode

Total characters604
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)4.2%

Sample

1st row30
2nd row0
3rd row35
4th row0
5th row0
ValueCountFrequency (%)
0 344
68.8%
1 21
 
4.2%
5 17
 
3.4%
10 13
 
2.6%
30 10
 
2.0%
20 10
 
2.0%
2 8
 
1.6%
40 8
 
1.6%
50 5
 
1.0%
6 4
 
0.8%
Other values (36) 60
 
12.0%
2023-12-09T22:15:24.530271image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 401
66.4%
1 57
 
9.4%
5 40
 
6.6%
2 39
 
6.5%
3 25
 
4.1%
4 16
 
2.6%
6 8
 
1.3%
7 8
 
1.3%
8 6
 
1.0%
9 4
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 604
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 401
66.4%
1 57
 
9.4%
5 40
 
6.6%
2 39
 
6.5%
3 25
 
4.1%
4 16
 
2.6%
6 8
 
1.3%
7 8
 
1.3%
8 6
 
1.0%
9 4
 
0.7%

Most occurring scripts

ValueCountFrequency (%)
Common 604
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 401
66.4%
1 57
 
9.4%
5 40
 
6.6%
2 39
 
6.5%
3 25
 
4.1%
4 16
 
2.6%
6 8
 
1.3%
7 8
 
1.3%
8 6
 
1.0%
9 4
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 604
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 401
66.4%
1 57
 
9.4%
5 40
 
6.6%
2 39
 
6.5%
3 25
 
4.1%
4 16
 
2.6%
6 8
 
1.3%
7 8
 
1.3%
8 6
 
1.0%
9 4
 
0.7%

q17_c4_r3
Text

MISSING 

Distinct27
Distinct (%)5.4%
Missing500
Missing (%)50.0%
Memory size44.1 KiB
2023-12-09T22:15:24.687842image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.122
Min length1

Characters and Unicode

Total characters561
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)1.8%

Sample

1st row0
2nd row0
3rd row0
4th row20
5th row0
ValueCountFrequency (%)
0 391
78.2%
5 16
 
3.2%
1 14
 
2.8%
10 14
 
2.8%
30 8
 
1.6%
2 7
 
1.4%
15 6
 
1.2%
20 6
 
1.2%
8 5
 
1.0%
25 4
 
0.8%
Other values (17) 29
 
5.8%
2023-12-09T22:15:24.984562image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 426
75.9%
1 47
 
8.4%
5 30
 
5.3%
2 22
 
3.9%
3 12
 
2.1%
8 7
 
1.2%
6 6
 
1.1%
7 5
 
0.9%
4 5
 
0.9%
9 1
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 426
75.9%
1 47
 
8.4%
5 30
 
5.3%
2 22
 
3.9%
3 12
 
2.1%
8 7
 
1.2%
6 6
 
1.1%
7 5
 
0.9%
4 5
 
0.9%
9 1
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Common 561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 426
75.9%
1 47
 
8.4%
5 30
 
5.3%
2 22
 
3.9%
3 12
 
2.1%
8 7
 
1.2%
6 6
 
1.1%
7 5
 
0.9%
4 5
 
0.9%
9 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 426
75.9%
1 47
 
8.4%
5 30
 
5.3%
2 22
 
3.9%
3 12
 
2.1%
8 7
 
1.2%
6 6
 
1.1%
7 5
 
0.9%
4 5
 
0.9%
9 1
 
0.2%

q17_c4_r4
Text

MISSING 

Distinct41
Distinct (%)8.2%
Missing500
Missing (%)50.0%
Memory size44.2 KiB
2023-12-09T22:15:25.167345image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.22
Min length1

Characters and Unicode

Total characters610
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)3.0%

Sample

1st row0
2nd row30
3rd row35
4th row0
5th row0
ValueCountFrequency (%)
0 344
68.8%
20 15
 
3.0%
10 14
 
2.8%
1 13
 
2.6%
30 11
 
2.2%
2 10
 
2.0%
5 10
 
2.0%
40 8
 
1.6%
8 6
 
1.2%
50 6
 
1.2%
Other values (31) 63
 
12.6%
2023-12-09T22:15:25.482911image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 410
67.2%
1 54
 
8.9%
2 39
 
6.4%
5 32
 
5.2%
3 24
 
3.9%
4 19
 
3.1%
8 12
 
2.0%
6 10
 
1.6%
9 5
 
0.8%
7 5
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 610
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 410
67.2%
1 54
 
8.9%
2 39
 
6.4%
5 32
 
5.2%
3 24
 
3.9%
4 19
 
3.1%
8 12
 
2.0%
6 10
 
1.6%
9 5
 
0.8%
7 5
 
0.8%

Most occurring scripts

ValueCountFrequency (%)
Common 610
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 410
67.2%
1 54
 
8.9%
2 39
 
6.4%
5 32
 
5.2%
3 24
 
3.9%
4 19
 
3.1%
8 12
 
2.0%
6 10
 
1.6%
9 5
 
0.8%
7 5
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 610
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 410
67.2%
1 54
 
8.9%
2 39
 
6.4%
5 32
 
5.2%
3 24
 
3.9%
4 19
 
3.1%
8 12
 
2.0%
6 10
 
1.6%
9 5
 
0.8%
7 5
 
0.8%

q17_c5_r1
Text

MISSING 

Distinct36
Distinct (%)8.0%
Missing551
Missing (%)55.1%
Memory size42.8 KiB
2023-12-09T22:15:25.655376image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.169265033
Min length1

Characters and Unicode

Total characters525
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)3.8%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row8
ValueCountFrequency (%)
0 318
70.8%
10 17
 
3.8%
1 17
 
3.8%
2 10
 
2.2%
20 9
 
2.0%
15 7
 
1.6%
5 7
 
1.6%
6 7
 
1.6%
8 7
 
1.6%
12 6
 
1.3%
Other values (26) 44
 
9.8%
2023-12-09T22:15:25.970335image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 357
68.0%
1 57
 
10.9%
2 35
 
6.7%
5 21
 
4.0%
3 16
 
3.0%
6 13
 
2.5%
8 10
 
1.9%
7 8
 
1.5%
4 5
 
1.0%
9 3
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 525
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 357
68.0%
1 57
 
10.9%
2 35
 
6.7%
5 21
 
4.0%
3 16
 
3.0%
6 13
 
2.5%
8 10
 
1.9%
7 8
 
1.5%
4 5
 
1.0%
9 3
 
0.6%

Most occurring scripts

ValueCountFrequency (%)
Common 525
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 357
68.0%
1 57
 
10.9%
2 35
 
6.7%
5 21
 
4.0%
3 16
 
3.0%
6 13
 
2.5%
8 10
 
1.9%
7 8
 
1.5%
4 5
 
1.0%
9 3
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 525
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 357
68.0%
1 57
 
10.9%
2 35
 
6.7%
5 21
 
4.0%
3 16
 
3.0%
6 13
 
2.5%
8 10
 
1.9%
7 8
 
1.5%
4 5
 
1.0%
9 3
 
0.6%

q17_c5_r2
Text

MISSING 

Distinct39
Distinct (%)8.7%
Missing551
Missing (%)55.1%
Memory size42.9 KiB
2023-12-09T22:15:26.147256image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.180400891
Min length1

Characters and Unicode

Total characters530
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)3.3%

Sample

1st row35
2nd row0
3rd row0
4th row0
5th row17
ValueCountFrequency (%)
0 318
70.8%
1 17
 
3.8%
5 13
 
2.9%
10 11
 
2.4%
2 8
 
1.8%
20 8
 
1.8%
30 8
 
1.8%
40 5
 
1.1%
15 5
 
1.1%
50 5
 
1.1%
Other values (29) 51
 
11.4%
2023-12-09T22:15:26.462164image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 360
67.9%
1 48
 
9.1%
5 33
 
6.2%
2 30
 
5.7%
3 20
 
3.8%
4 14
 
2.6%
7 9
 
1.7%
6 7
 
1.3%
8 6
 
1.1%
9 3
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 530
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 360
67.9%
1 48
 
9.1%
5 33
 
6.2%
2 30
 
5.7%
3 20
 
3.8%
4 14
 
2.6%
7 9
 
1.7%
6 7
 
1.3%
8 6
 
1.1%
9 3
 
0.6%

Most occurring scripts

ValueCountFrequency (%)
Common 530
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 360
67.9%
1 48
 
9.1%
5 33
 
6.2%
2 30
 
5.7%
3 20
 
3.8%
4 14
 
2.6%
7 9
 
1.7%
6 7
 
1.3%
8 6
 
1.1%
9 3
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 530
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 360
67.9%
1 48
 
9.1%
5 33
 
6.2%
2 30
 
5.7%
3 20
 
3.8%
4 14
 
2.6%
7 9
 
1.7%
6 7
 
1.3%
8 6
 
1.1%
9 3
 
0.6%

q17_c5_r3
Text

MISSING 

Distinct24
Distinct (%)5.3%
Missing551
Missing (%)55.1%
Memory size42.8 KiB
2023-12-09T22:15:26.613907image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.100222717
Min length1

Characters and Unicode

Total characters494
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)1.8%

Sample

1st row0
2nd row20
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 357
79.5%
5 12
 
2.7%
1 12
 
2.7%
10 11
 
2.4%
8 7
 
1.6%
2 7
 
1.6%
30 7
 
1.6%
20 7
 
1.6%
15 6
 
1.3%
7 3
 
0.7%
Other values (14) 20
 
4.5%
2023-12-09T22:15:26.898661image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 384
77.7%
1 36
 
7.3%
5 23
 
4.7%
2 19
 
3.8%
3 11
 
2.2%
8 8
 
1.6%
6 5
 
1.0%
4 4
 
0.8%
7 3
 
0.6%
9 1
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 494
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 384
77.7%
1 36
 
7.3%
5 23
 
4.7%
2 19
 
3.8%
3 11
 
2.2%
8 8
 
1.6%
6 5
 
1.0%
4 4
 
0.8%
7 3
 
0.6%
9 1
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Common 494
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 384
77.7%
1 36
 
7.3%
5 23
 
4.7%
2 19
 
3.8%
3 11
 
2.2%
8 8
 
1.6%
6 5
 
1.0%
4 4
 
0.8%
7 3
 
0.6%
9 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 494
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 384
77.7%
1 36
 
7.3%
5 23
 
4.7%
2 19
 
3.8%
3 11
 
2.2%
8 8
 
1.6%
6 5
 
1.0%
4 4
 
0.8%
7 3
 
0.6%
9 1
 
0.2%

q17_c5_r4
Text

MISSING 

Distinct39
Distinct (%)8.7%
Missing551
Missing (%)55.1%
Memory size42.9 KiB
2023-12-09T22:15:27.076363image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.189309577
Min length1

Characters and Unicode

Total characters534
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)3.8%

Sample

1st row35
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 320
71.3%
10 12
 
2.7%
1 12
 
2.7%
2 11
 
2.4%
20 11
 
2.4%
40 8
 
1.8%
5 7
 
1.6%
30 6
 
1.3%
8 6
 
1.3%
18 4
 
0.9%
Other values (29) 52
 
11.6%
2023-12-09T22:15:27.404505image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 371
69.5%
1 43
 
8.1%
2 32
 
6.0%
5 23
 
4.3%
3 20
 
3.7%
4 15
 
2.8%
8 12
 
2.2%
6 8
 
1.5%
7 6
 
1.1%
9 4
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 534
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 371
69.5%
1 43
 
8.1%
2 32
 
6.0%
5 23
 
4.3%
3 20
 
3.7%
4 15
 
2.8%
8 12
 
2.2%
6 8
 
1.5%
7 6
 
1.1%
9 4
 
0.7%

Most occurring scripts

ValueCountFrequency (%)
Common 534
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 371
69.5%
1 43
 
8.1%
2 32
 
6.0%
5 23
 
4.3%
3 20
 
3.7%
4 15
 
2.8%
8 12
 
2.2%
6 8
 
1.5%
7 6
 
1.1%
9 4
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 534
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 371
69.5%
1 43
 
8.1%
2 32
 
6.0%
5 23
 
4.3%
3 20
 
3.7%
4 15
 
2.8%
8 12
 
2.2%
6 8
 
1.5%
7 6
 
1.1%
9 4
 
0.7%

q17_c6_r1
Text

MISSING 

Distinct29
Distinct (%)7.6%
Missing617
Missing (%)61.7%
Memory size41.2 KiB
2023-12-09T22:15:27.563867image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.164490862
Min length1

Characters and Unicode

Total characters446
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)2.6%

Sample

1st row0
2nd row0
3rd row4
4th row0
5th row3
ValueCountFrequency (%)
0 275
71.8%
10 16
 
4.2%
1 14
 
3.7%
20 10
 
2.6%
2 7
 
1.8%
5 6
 
1.6%
6 6
 
1.6%
8 6
 
1.6%
15 5
 
1.3%
30 5
 
1.3%
Other values (19) 33
 
8.6%
2023-12-09T22:15:27.855913image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 309
69.3%
1 46
 
10.3%
2 29
 
6.5%
3 16
 
3.6%
5 15
 
3.4%
6 13
 
2.9%
8 8
 
1.8%
4 4
 
0.9%
7 4
 
0.9%
9 2
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 446
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 309
69.3%
1 46
 
10.3%
2 29
 
6.5%
3 16
 
3.6%
5 15
 
3.4%
6 13
 
2.9%
8 8
 
1.8%
4 4
 
0.9%
7 4
 
0.9%
9 2
 
0.4%

Most occurring scripts

ValueCountFrequency (%)
Common 446
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 309
69.3%
1 46
 
10.3%
2 29
 
6.5%
3 16
 
3.6%
5 15
 
3.4%
6 13
 
2.9%
8 8
 
1.8%
4 4
 
0.9%
7 4
 
0.9%
9 2
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 446
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 309
69.3%
1 46
 
10.3%
2 29
 
6.5%
3 16
 
3.6%
5 15
 
3.4%
6 13
 
2.9%
8 8
 
1.8%
4 4
 
0.9%
7 4
 
0.9%
9 2
 
0.4%

q17_c6_r2
Text

MISSING 

Distinct34
Distinct (%)8.9%
Missing617
Missing (%)61.7%
Memory size41.2 KiB
2023-12-09T22:15:28.025052image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.167101828
Min length1

Characters and Unicode

Total characters447
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)3.9%

Sample

1st row35
2nd row0
3rd row5
4th row0
5th row0
ValueCountFrequency (%)
0 275
71.8%
1 16
 
4.2%
5 12
 
3.1%
20 9
 
2.3%
10 8
 
2.1%
2 7
 
1.8%
40 6
 
1.6%
30 6
 
1.6%
15 4
 
1.0%
8 4
 
1.0%
Other values (24) 36
 
9.4%
2023-12-09T22:15:28.340733image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 312
69.8%
1 37
 
8.3%
5 26
 
5.8%
2 26
 
5.8%
3 16
 
3.6%
4 13
 
2.9%
6 6
 
1.3%
8 5
 
1.1%
7 4
 
0.9%
9 2
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 447
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 312
69.8%
1 37
 
8.3%
5 26
 
5.8%
2 26
 
5.8%
3 16
 
3.6%
4 13
 
2.9%
6 6
 
1.3%
8 5
 
1.1%
7 4
 
0.9%
9 2
 
0.4%

Most occurring scripts

ValueCountFrequency (%)
Common 447
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 312
69.8%
1 37
 
8.3%
5 26
 
5.8%
2 26
 
5.8%
3 16
 
3.6%
4 13
 
2.9%
6 6
 
1.3%
8 5
 
1.1%
7 4
 
0.9%
9 2
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 447
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 312
69.8%
1 37
 
8.3%
5 26
 
5.8%
2 26
 
5.8%
3 16
 
3.6%
4 13
 
2.9%
6 6
 
1.3%
8 5
 
1.1%
7 4
 
0.9%
9 2
 
0.4%

q17_c6_r3
Text

MISSING 

Distinct20
Distinct (%)5.2%
Missing617
Missing (%)61.7%
Memory size41.1 KiB
2023-12-09T22:15:28.486200image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.093994778
Min length1

Characters and Unicode

Total characters419
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)1.6%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 312
81.5%
10 10
 
2.6%
5 8
 
2.1%
1 7
 
1.8%
2 6
 
1.6%
15 6
 
1.6%
8 6
 
1.6%
20 6
 
1.6%
30 6
 
1.6%
4 2
 
0.5%
Other values (10) 14
 
3.7%
2023-12-09T22:15:28.752167image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 334
79.7%
1 27
 
6.4%
5 17
 
4.1%
2 15
 
3.6%
3 10
 
2.4%
8 6
 
1.4%
6 4
 
1.0%
4 3
 
0.7%
7 2
 
0.5%
9 1
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 419
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 334
79.7%
1 27
 
6.4%
5 17
 
4.1%
2 15
 
3.6%
3 10
 
2.4%
8 6
 
1.4%
6 4
 
1.0%
4 3
 
0.7%
7 2
 
0.5%
9 1
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Common 419
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 334
79.7%
1 27
 
6.4%
5 17
 
4.1%
2 15
 
3.6%
3 10
 
2.4%
8 6
 
1.4%
6 4
 
1.0%
4 3
 
0.7%
7 2
 
0.5%
9 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 419
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 334
79.7%
1 27
 
6.4%
5 17
 
4.1%
2 15
 
3.6%
3 10
 
2.4%
8 6
 
1.4%
6 4
 
1.0%
4 3
 
0.7%
7 2
 
0.5%
9 1
 
0.2%

q17_c6_r4
Text

MISSING 

Distinct38
Distinct (%)9.9%
Missing617
Missing (%)61.7%
Memory size41.2 KiB
2023-12-09T22:15:28.928725image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.195822454
Min length1

Characters and Unicode

Total characters458
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)5.2%

Sample

1st row35
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 273
71.3%
10 11
 
2.9%
20 11
 
2.9%
2 10
 
2.6%
1 8
 
2.1%
40 8
 
2.1%
5 6
 
1.6%
8 6
 
1.6%
18 4
 
1.0%
15 4
 
1.0%
Other values (28) 42
 
11.0%
2023-12-09T22:15:29.247332image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 316
69.0%
1 38
 
8.3%
2 27
 
5.9%
5 20
 
4.4%
3 19
 
4.1%
4 13
 
2.8%
8 12
 
2.6%
6 6
 
1.3%
7 4
 
0.9%
9 3
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 458
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 316
69.0%
1 38
 
8.3%
2 27
 
5.9%
5 20
 
4.4%
3 19
 
4.1%
4 13
 
2.8%
8 12
 
2.6%
6 6
 
1.3%
7 4
 
0.9%
9 3
 
0.7%

Most occurring scripts

ValueCountFrequency (%)
Common 458
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 316
69.0%
1 38
 
8.3%
2 27
 
5.9%
5 20
 
4.4%
3 19
 
4.1%
4 13
 
2.8%
8 12
 
2.6%
6 6
 
1.3%
7 4
 
0.9%
9 3
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 458
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 316
69.0%
1 38
 
8.3%
2 27
 
5.9%
5 20
 
4.4%
3 19
 
4.1%
4 13
 
2.8%
8 12
 
2.6%
6 6
 
1.3%
7 4
 
0.9%
9 3
 
0.7%

q17_c7_r1
Text

MISSING 

Distinct27
Distinct (%)8.4%
Missing679
Missing (%)67.9%
Memory size39.6 KiB
2023-12-09T22:15:29.407714image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.165109034
Min length1

Characters and Unicode

Total characters374
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)2.2%

Sample

1st row0
2nd row4
3rd row0
4th row3
5th row0
ValueCountFrequency (%)
0 234
72.9%
1 12
 
3.7%
10 11
 
3.4%
20 8
 
2.5%
6 6
 
1.9%
15 5
 
1.6%
30 5
 
1.6%
2 5
 
1.6%
25 3
 
0.9%
8 3
 
0.9%
Other values (17) 29
 
9.0%
2023-12-09T22:15:29.697311image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 261
69.8%
1 38
 
10.2%
2 22
 
5.9%
3 15
 
4.0%
6 13
 
3.5%
5 11
 
2.9%
8 5
 
1.3%
7 4
 
1.1%
4 3
 
0.8%
9 2
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 374
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 261
69.8%
1 38
 
10.2%
2 22
 
5.9%
3 15
 
4.0%
6 13
 
3.5%
5 11
 
2.9%
8 5
 
1.3%
7 4
 
1.1%
4 3
 
0.8%
9 2
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
Common 374
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 261
69.8%
1 38
 
10.2%
2 22
 
5.9%
3 15
 
4.0%
6 13
 
3.5%
5 11
 
2.9%
8 5
 
1.3%
7 4
 
1.1%
4 3
 
0.8%
9 2
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 374
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 261
69.8%
1 38
 
10.2%
2 22
 
5.9%
3 15
 
4.0%
6 13
 
3.5%
5 11
 
2.9%
8 5
 
1.3%
7 4
 
1.1%
4 3
 
0.8%
9 2
 
0.5%

q17_c7_r2
Text

MISSING 

Distinct33
Distinct (%)10.3%
Missing679
Missing (%)67.9%
Memory size39.6 KiB
2023-12-09T22:15:29.862553image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.180685358
Min length1

Characters and Unicode

Total characters379
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)5.0%

Sample

1st row35
2nd row5
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 234
72.9%
1 9
 
2.8%
10 8
 
2.5%
5 7
 
2.2%
40 6
 
1.9%
20 6
 
1.9%
30 5
 
1.6%
8 5
 
1.6%
15 4
 
1.2%
2 4
 
1.2%
Other values (23) 33
 
10.3%
2023-12-09T22:15:30.167687image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 265
69.9%
1 30
 
7.9%
5 21
 
5.5%
2 20
 
5.3%
3 15
 
4.0%
4 10
 
2.6%
8 6
 
1.6%
6 6
 
1.6%
7 4
 
1.1%
9 2
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 379
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 265
69.9%
1 30
 
7.9%
5 21
 
5.5%
2 20
 
5.3%
3 15
 
4.0%
4 10
 
2.6%
8 6
 
1.6%
6 6
 
1.6%
7 4
 
1.1%
9 2
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
Common 379
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 265
69.9%
1 30
 
7.9%
5 21
 
5.5%
2 20
 
5.3%
3 15
 
4.0%
4 10
 
2.6%
8 6
 
1.6%
6 6
 
1.6%
7 4
 
1.1%
9 2
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 379
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 265
69.9%
1 30
 
7.9%
5 21
 
5.5%
2 20
 
5.3%
3 15
 
4.0%
4 10
 
2.6%
8 6
 
1.6%
6 6
 
1.6%
7 4
 
1.1%
9 2
 
0.5%

q17_c7_r3
Text

MISSING 

Distinct18
Distinct (%)5.6%
Missing679
Missing (%)67.9%
Memory size39.6 KiB
2023-12-09T22:15:30.312231image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.099688474
Min length1

Characters and Unicode

Total characters353
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)1.6%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 266
82.9%
10 9
 
2.8%
30 6
 
1.9%
20 5
 
1.6%
1 5
 
1.6%
15 5
 
1.6%
5 4
 
1.2%
2 4
 
1.2%
8 4
 
1.2%
4 2
 
0.6%
Other values (8) 11
 
3.4%
2023-12-09T22:15:30.574317image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 286
81.0%
1 23
 
6.5%
2 12
 
3.4%
5 11
 
3.1%
3 10
 
2.8%
8 4
 
1.1%
6 3
 
0.8%
4 2
 
0.6%
9 1
 
0.3%
7 1
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 353
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 286
81.0%
1 23
 
6.5%
2 12
 
3.4%
5 11
 
3.1%
3 10
 
2.8%
8 4
 
1.1%
6 3
 
0.8%
4 2
 
0.6%
9 1
 
0.3%
7 1
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
Common 353
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 286
81.0%
1 23
 
6.5%
2 12
 
3.4%
5 11
 
3.1%
3 10
 
2.8%
8 4
 
1.1%
6 3
 
0.8%
4 2
 
0.6%
9 1
 
0.3%
7 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 353
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 286
81.0%
1 23
 
6.5%
2 12
 
3.4%
5 11
 
3.1%
3 10
 
2.8%
8 4
 
1.1%
6 3
 
0.8%
4 2
 
0.6%
9 1
 
0.3%
7 1
 
0.3%

q17_c7_r4
Text

MISSING 

Distinct34
Distinct (%)10.6%
Missing679
Missing (%)67.9%
Memory size39.6 KiB
2023-12-09T22:15:30.744454image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.186915888
Min length1

Characters and Unicode

Total characters381
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)4.7%

Sample

1st row35
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 237
73.8%
20 8
 
2.5%
10 7
 
2.2%
1 6
 
1.9%
40 6
 
1.9%
8 5
 
1.6%
5 4
 
1.2%
2 4
 
1.2%
30 4
 
1.2%
3 4
 
1.2%
Other values (24) 36
 
11.2%
2023-12-09T22:15:31.053840image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 270
70.9%
1 31
 
8.1%
2 17
 
4.5%
5 17
 
4.5%
3 15
 
3.9%
4 10
 
2.6%
8 10
 
2.6%
6 6
 
1.6%
9 3
 
0.8%
7 2
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 381
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 270
70.9%
1 31
 
8.1%
2 17
 
4.5%
5 17
 
4.5%
3 15
 
3.9%
4 10
 
2.6%
8 10
 
2.6%
6 6
 
1.6%
9 3
 
0.8%
7 2
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
Common 381
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 270
70.9%
1 31
 
8.1%
2 17
 
4.5%
5 17
 
4.5%
3 15
 
3.9%
4 10
 
2.6%
8 10
 
2.6%
6 6
 
1.6%
9 3
 
0.8%
7 2
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 381
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 270
70.9%
1 31
 
8.1%
2 17
 
4.5%
5 17
 
4.5%
3 15
 
3.9%
4 10
 
2.6%
8 10
 
2.6%
6 6
 
1.6%
9 3
 
0.8%
7 2
 
0.5%

q17_c8_r1
Text

MISSING 

Distinct25
Distinct (%)9.4%
Missing734
Missing (%)73.4%
Memory size38.2 KiB
2023-12-09T22:15:31.213481image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.161654135
Min length1

Characters and Unicode

Total characters309
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)2.3%

Sample

1st row0
2nd row4
3rd row0
4th row3
5th row0
ValueCountFrequency (%)
0 194
72.9%
10 10
 
3.8%
1 7
 
2.6%
20 7
 
2.6%
6 5
 
1.9%
15 4
 
1.5%
30 4
 
1.5%
2 4
 
1.5%
25 3
 
1.1%
8 3
 
1.1%
Other values (15) 25
 
9.4%
2023-12-09T22:15:31.493447image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 218
70.6%
1 27
 
8.7%
2 20
 
6.5%
3 12
 
3.9%
6 10
 
3.2%
5 10
 
3.2%
8 4
 
1.3%
4 3
 
1.0%
7 3
 
1.0%
9 2
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 309
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 218
70.6%
1 27
 
8.7%
2 20
 
6.5%
3 12
 
3.9%
6 10
 
3.2%
5 10
 
3.2%
8 4
 
1.3%
4 3
 
1.0%
7 3
 
1.0%
9 2
 
0.6%

Most occurring scripts

ValueCountFrequency (%)
Common 309
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 218
70.6%
1 27
 
8.7%
2 20
 
6.5%
3 12
 
3.9%
6 10
 
3.2%
5 10
 
3.2%
8 4
 
1.3%
4 3
 
1.0%
7 3
 
1.0%
9 2
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 309
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 218
70.6%
1 27
 
8.7%
2 20
 
6.5%
3 12
 
3.9%
6 10
 
3.2%
5 10
 
3.2%
8 4
 
1.3%
4 3
 
1.0%
7 3
 
1.0%
9 2
 
0.6%

q17_c8_r2
Text

MISSING 

Distinct31
Distinct (%)11.7%
Missing734
Missing (%)73.4%
Memory size38.2 KiB
2023-12-09T22:15:31.659714image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.169172932
Min length1

Characters and Unicode

Total characters311
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)6.0%

Sample

1st row35
2nd row5
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 196
73.7%
1 7
 
2.6%
10 6
 
2.3%
5 6
 
2.3%
40 5
 
1.9%
30 5
 
1.9%
20 5
 
1.9%
8 4
 
1.5%
7 3
 
1.1%
6 3
 
1.1%
Other values (21) 26
 
9.8%
2023-12-09T22:15:32.710263image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 221
71.1%
1 21
 
6.8%
2 16
 
5.1%
5 15
 
4.8%
3 12
 
3.9%
4 9
 
2.9%
6 6
 
1.9%
8 5
 
1.6%
7 5
 
1.6%
9 1
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 311
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 221
71.1%
1 21
 
6.8%
2 16
 
5.1%
5 15
 
4.8%
3 12
 
3.9%
4 9
 
2.9%
6 6
 
1.9%
8 5
 
1.6%
7 5
 
1.6%
9 1
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
Common 311
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 221
71.1%
1 21
 
6.8%
2 16
 
5.1%
5 15
 
4.8%
3 12
 
3.9%
4 9
 
2.9%
6 6
 
1.9%
8 5
 
1.6%
7 5
 
1.6%
9 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 311
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 221
71.1%
1 21
 
6.8%
2 16
 
5.1%
5 15
 
4.8%
3 12
 
3.9%
4 9
 
2.9%
6 6
 
1.9%
8 5
 
1.6%
7 5
 
1.6%
9 1
 
0.3%

q17_c8_r3
Text

MISSING 

Distinct18
Distinct (%)6.8%
Missing734
Missing (%)73.4%
Memory size38.2 KiB
2023-12-09T22:15:32.851588image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.097744361
Min length1

Characters and Unicode

Total characters292
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)2.6%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 222
83.5%
10 6
 
2.3%
8 5
 
1.9%
1 4
 
1.5%
30 4
 
1.5%
15 4
 
1.5%
20 4
 
1.5%
5 3
 
1.1%
2 3
 
1.1%
12 2
 
0.8%
Other values (8) 9
 
3.4%
2023-12-09T22:15:33.117440image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 236
80.8%
1 18
 
6.2%
2 10
 
3.4%
5 9
 
3.1%
3 7
 
2.4%
8 6
 
2.1%
6 3
 
1.0%
4 1
 
0.3%
9 1
 
0.3%
7 1
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 292
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 236
80.8%
1 18
 
6.2%
2 10
 
3.4%
5 9
 
3.1%
3 7
 
2.4%
8 6
 
2.1%
6 3
 
1.0%
4 1
 
0.3%
9 1
 
0.3%
7 1
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
Common 292
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 236
80.8%
1 18
 
6.2%
2 10
 
3.4%
5 9
 
3.1%
3 7
 
2.4%
8 6
 
2.1%
6 3
 
1.0%
4 1
 
0.3%
9 1
 
0.3%
7 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 292
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 236
80.8%
1 18
 
6.2%
2 10
 
3.4%
5 9
 
3.1%
3 7
 
2.4%
8 6
 
2.1%
6 3
 
1.0%
4 1
 
0.3%
9 1
 
0.3%
7 1
 
0.3%

q17_c8_r4
Text

MISSING 

Distinct30
Distinct (%)11.3%
Missing734
Missing (%)73.4%
Memory size38.2 KiB
2023-12-09T22:15:33.284809image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.180451128
Min length1

Characters and Unicode

Total characters314
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)5.3%

Sample

1st row35
2nd row0
3rd row0
4th row1
5th row0
ValueCountFrequency (%)
0 196
73.7%
20 9
 
3.4%
1 7
 
2.6%
10 7
 
2.6%
40 5
 
1.9%
8 4
 
1.5%
5 3
 
1.1%
30 3
 
1.1%
18 3
 
1.1%
9 3
 
1.1%
Other values (20) 26
 
9.8%
2023-12-09T22:15:33.579228image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 222
70.7%
1 27
 
8.6%
2 14
 
4.5%
5 13
 
4.1%
3 12
 
3.8%
4 9
 
2.9%
8 8
 
2.5%
6 4
 
1.3%
9 3
 
1.0%
7 2
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 314
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 222
70.7%
1 27
 
8.6%
2 14
 
4.5%
5 13
 
4.1%
3 12
 
3.8%
4 9
 
2.9%
8 8
 
2.5%
6 4
 
1.3%
9 3
 
1.0%
7 2
 
0.6%

Most occurring scripts

ValueCountFrequency (%)
Common 314
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 222
70.7%
1 27
 
8.6%
2 14
 
4.5%
5 13
 
4.1%
3 12
 
3.8%
4 9
 
2.9%
8 8
 
2.5%
6 4
 
1.3%
9 3
 
1.0%
7 2
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 314
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 222
70.7%
1 27
 
8.6%
2 14
 
4.5%
5 13
 
4.1%
3 12
 
3.8%
4 9
 
2.9%
8 8
 
2.5%
6 4
 
1.3%
9 3
 
1.0%
7 2
 
0.6%

q17_c9_r1
Text

MISSING 

Distinct22
Distinct (%)11.5%
Missing808
Missing (%)80.8%
Memory size36.3 KiB
2023-12-09T22:15:33.728402image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.145833333
Min length1

Characters and Unicode

Total characters220
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)4.7%

Sample

1st row4
2nd row0
3rd row10
4th row0
5th row0
ValueCountFrequency (%)
0 141
73.4%
10 8
 
4.2%
1 7
 
3.6%
20 5
 
2.6%
6 4
 
2.1%
25 3
 
1.6%
2 3
 
1.6%
15 2
 
1.0%
4 2
 
1.0%
23 2
 
1.0%
Other values (12) 15
 
7.8%
2023-12-09T22:15:34.003082image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 158
71.8%
1 20
 
9.1%
2 14
 
6.4%
5 7
 
3.2%
3 7
 
3.2%
6 5
 
2.3%
8 3
 
1.4%
4 3
 
1.4%
9 2
 
0.9%
7 1
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 220
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 158
71.8%
1 20
 
9.1%
2 14
 
6.4%
5 7
 
3.2%
3 7
 
3.2%
6 5
 
2.3%
8 3
 
1.4%
4 3
 
1.4%
9 2
 
0.9%
7 1
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
Common 220
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 158
71.8%
1 20
 
9.1%
2 14
 
6.4%
5 7
 
3.2%
3 7
 
3.2%
6 5
 
2.3%
8 3
 
1.4%
4 3
 
1.4%
9 2
 
0.9%
7 1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 158
71.8%
1 20
 
9.1%
2 14
 
6.4%
5 7
 
3.2%
3 7
 
3.2%
6 5
 
2.3%
8 3
 
1.4%
4 3
 
1.4%
9 2
 
0.9%
7 1
 
0.5%

q17_c9_r2
Text

MISSING 

Distinct25
Distinct (%)13.0%
Missing808
Missing (%)80.8%
Memory size36.3 KiB
2023-12-09T22:15:34.160187image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.151041667
Min length1

Characters and Unicode

Total characters221
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)7.8%

Sample

1st row5
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 140
72.9%
5 7
 
3.6%
1 7
 
3.6%
40 5
 
2.6%
10 5
 
2.6%
20 4
 
2.1%
6 3
 
1.6%
8 2
 
1.0%
2 2
 
1.0%
30 2
 
1.0%
Other values (15) 15
 
7.8%
2023-12-09T22:15:34.461973image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 159
71.9%
1 15
 
6.8%
5 14
 
6.3%
2 10
 
4.5%
4 7
 
3.2%
6 5
 
2.3%
3 5
 
2.3%
7 3
 
1.4%
8 2
 
0.9%
9 1
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 221
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 159
71.9%
1 15
 
6.8%
5 14
 
6.3%
2 10
 
4.5%
4 7
 
3.2%
6 5
 
2.3%
3 5
 
2.3%
7 3
 
1.4%
8 2
 
0.9%
9 1
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
Common 221
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 159
71.9%
1 15
 
6.8%
5 14
 
6.3%
2 10
 
4.5%
4 7
 
3.2%
6 5
 
2.3%
3 5
 
2.3%
7 3
 
1.4%
8 2
 
0.9%
9 1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 221
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 159
71.9%
1 15
 
6.8%
5 14
 
6.3%
2 10
 
4.5%
4 7
 
3.2%
6 5
 
2.3%
3 5
 
2.3%
7 3
 
1.4%
8 2
 
0.9%
9 1
 
0.5%

q17_c9_r3
Text

MISSING 

Distinct17
Distinct (%)8.9%
Missing808
Missing (%)80.8%
Memory size36.3 KiB
2023-12-09T22:15:34.602324image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.088541667
Min length1

Characters and Unicode

Total characters209
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)3.6%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 161
83.9%
20 4
 
2.1%
8 3
 
1.6%
10 3
 
1.6%
30 3
 
1.6%
1 3
 
1.6%
15 2
 
1.0%
5 2
 
1.0%
12 2
 
1.0%
2 2
 
1.0%
Other values (7) 7
 
3.6%
2023-12-09T22:15:34.877152image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 171
81.8%
1 11
 
5.3%
2 9
 
4.3%
5 5
 
2.4%
3 4
 
1.9%
8 3
 
1.4%
6 3
 
1.4%
4 1
 
0.5%
9 1
 
0.5%
7 1
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 209
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 171
81.8%
1 11
 
5.3%
2 9
 
4.3%
5 5
 
2.4%
3 4
 
1.9%
8 3
 
1.4%
6 3
 
1.4%
4 1
 
0.5%
9 1
 
0.5%
7 1
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
Common 209
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 171
81.8%
1 11
 
5.3%
2 9
 
4.3%
5 5
 
2.4%
3 4
 
1.9%
8 3
 
1.4%
6 3
 
1.4%
4 1
 
0.5%
9 1
 
0.5%
7 1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 209
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 171
81.8%
1 11
 
5.3%
2 9
 
4.3%
5 5
 
2.4%
3 4
 
1.9%
8 3
 
1.4%
6 3
 
1.4%
4 1
 
0.5%
9 1
 
0.5%
7 1
 
0.5%

q17_c9_r4
Text

MISSING 

Distinct24
Distinct (%)12.5%
Missing808
Missing (%)80.8%
Memory size36.3 KiB
2023-12-09T22:15:35.040854image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.145833333
Min length1

Characters and Unicode

Total characters220
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)6.2%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 146
76.0%
20 5
 
2.6%
1 5
 
2.6%
8 4
 
2.1%
10 4
 
2.1%
18 3
 
1.6%
6 3
 
1.6%
40 2
 
1.0%
3 2
 
1.0%
15 2
 
1.0%
Other values (14) 16
 
8.3%
2023-12-09T22:15:35.351734image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 159
72.3%
1 17
 
7.7%
5 9
 
4.1%
2 8
 
3.6%
8 8
 
3.6%
3 7
 
3.2%
4 5
 
2.3%
6 4
 
1.8%
9 2
 
0.9%
7 1
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 220
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 159
72.3%
1 17
 
7.7%
5 9
 
4.1%
2 8
 
3.6%
8 8
 
3.6%
3 7
 
3.2%
4 5
 
2.3%
6 4
 
1.8%
9 2
 
0.9%
7 1
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
Common 220
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 159
72.3%
1 17
 
7.7%
5 9
 
4.1%
2 8
 
3.6%
8 8
 
3.6%
3 7
 
3.2%
4 5
 
2.3%
6 4
 
1.8%
9 2
 
0.9%
7 1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 159
72.3%
1 17
 
7.7%
5 9
 
4.1%
2 8
 
3.6%
8 8
 
3.6%
3 7
 
3.2%
4 5
 
2.3%
6 4
 
1.8%
9 2
 
0.9%
7 1
 
0.5%

q17_c10_r1
Text

MISSING 

Distinct19
Distinct (%)13.0%
Missing854
Missing (%)85.4%
Memory size35.1 KiB
2023-12-09T22:15:35.501738image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.143835616
Min length1

Characters and Unicode

Total characters167
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)5.5%

Sample

1st row4
2nd row0
3rd row10
4th row0
5th row25
ValueCountFrequency (%)
0 107
73.3%
1 5
 
3.4%
10 5
 
3.4%
2 4
 
2.7%
20 4
 
2.7%
6 3
 
2.1%
30 2
 
1.4%
15 2
 
1.4%
12 2
 
1.4%
8 2
 
1.4%
Other values (9) 10
 
6.8%
2023-12-09T22:15:35.778240image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 118
70.7%
1 16
 
9.6%
2 13
 
7.8%
3 6
 
3.6%
6 4
 
2.4%
5 4
 
2.4%
8 3
 
1.8%
9 1
 
0.6%
4 1
 
0.6%
7 1
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 167
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 118
70.7%
1 16
 
9.6%
2 13
 
7.8%
3 6
 
3.6%
6 4
 
2.4%
5 4
 
2.4%
8 3
 
1.8%
9 1
 
0.6%
4 1
 
0.6%
7 1
 
0.6%

Most occurring scripts

ValueCountFrequency (%)
Common 167
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 118
70.7%
1 16
 
9.6%
2 13
 
7.8%
3 6
 
3.6%
6 4
 
2.4%
5 4
 
2.4%
8 3
 
1.8%
9 1
 
0.6%
4 1
 
0.6%
7 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 167
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 118
70.7%
1 16
 
9.6%
2 13
 
7.8%
3 6
 
3.6%
6 4
 
2.4%
5 4
 
2.4%
8 3
 
1.8%
9 1
 
0.6%
4 1
 
0.6%
7 1
 
0.6%

q17_c10_r2
Text

MISSING 

Distinct21
Distinct (%)14.4%
Missing854
Missing (%)85.4%
Memory size35.1 KiB
2023-12-09T22:15:35.928531image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.143835616
Min length1

Characters and Unicode

Total characters167
Distinct characters9
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)8.2%

Sample

1st row5
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 107
73.3%
1 6
 
4.1%
10 4
 
2.7%
5 4
 
2.7%
40 3
 
2.1%
20 3
 
2.1%
2 3
 
2.1%
8 2
 
1.4%
30 2
 
1.4%
4 1
 
0.7%
Other values (11) 11
 
7.5%
2023-12-09T22:15:36.216785image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 122
73.1%
1 11
 
6.6%
5 9
 
5.4%
2 9
 
5.4%
4 5
 
3.0%
3 4
 
2.4%
6 3
 
1.8%
8 2
 
1.2%
7 2
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 167
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 122
73.1%
1 11
 
6.6%
5 9
 
5.4%
2 9
 
5.4%
4 5
 
3.0%
3 4
 
2.4%
6 3
 
1.8%
8 2
 
1.2%
7 2
 
1.2%

Most occurring scripts

ValueCountFrequency (%)
Common 167
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 122
73.1%
1 11
 
6.6%
5 9
 
5.4%
2 9
 
5.4%
4 5
 
3.0%
3 4
 
2.4%
6 3
 
1.8%
8 2
 
1.2%
7 2
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 167
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 122
73.1%
1 11
 
6.6%
5 9
 
5.4%
2 9
 
5.4%
4 5
 
3.0%
3 4
 
2.4%
6 3
 
1.8%
8 2
 
1.2%
7 2
 
1.2%

q17_c10_r3
Text

MISSING 

Distinct14
Distinct (%)9.6%
Missing854
Missing (%)85.4%
Memory size35.1 KiB
2023-12-09T22:15:36.357397image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.095890411
Min length1

Characters and Unicode

Total characters160
Distinct characters9
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)4.1%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 124
84.9%
30 3
 
2.1%
10 3
 
2.1%
12 2
 
1.4%
2 2
 
1.4%
8 2
 
1.4%
20 2
 
1.4%
1 2
 
1.4%
25 1
 
0.7%
36 1
 
0.7%
Other values (4) 4
 
2.7%
2023-12-09T22:15:36.625614image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 132
82.5%
1 9
 
5.6%
2 7
 
4.4%
3 4
 
2.5%
8 2
 
1.2%
5 2
 
1.2%
6 2
 
1.2%
7 1
 
0.6%
4 1
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 160
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 132
82.5%
1 9
 
5.6%
2 7
 
4.4%
3 4
 
2.5%
8 2
 
1.2%
5 2
 
1.2%
6 2
 
1.2%
7 1
 
0.6%
4 1
 
0.6%

Most occurring scripts

ValueCountFrequency (%)
Common 160
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 132
82.5%
1 9
 
5.6%
2 7
 
4.4%
3 4
 
2.5%
8 2
 
1.2%
5 2
 
1.2%
6 2
 
1.2%
7 1
 
0.6%
4 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 160
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 132
82.5%
1 9
 
5.6%
2 7
 
4.4%
3 4
 
2.5%
8 2
 
1.2%
5 2
 
1.2%
6 2
 
1.2%
7 1
 
0.6%
4 1
 
0.6%

q17_c10_r4
Text

MISSING 

Distinct22
Distinct (%)15.1%
Missing854
Missing (%)85.4%
Memory size35.1 KiB
2023-12-09T22:15:36.776395image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.130136986
Min length1

Characters and Unicode

Total characters165
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)8.9%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 111
76.0%
8 5
 
3.4%
1 4
 
2.7%
10 3
 
2.1%
4 2
 
1.4%
6 2
 
1.4%
15 2
 
1.4%
20 2
 
1.4%
3 2
 
1.4%
18 1
 
0.7%
Other values (12) 12
 
8.2%
2023-12-09T22:15:37.078478image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 119
72.1%
1 12
 
7.3%
8 7
 
4.2%
5 6
 
3.6%
3 6
 
3.6%
4 5
 
3.0%
2 5
 
3.0%
6 3
 
1.8%
7 1
 
0.6%
9 1
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 165
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 119
72.1%
1 12
 
7.3%
8 7
 
4.2%
5 6
 
3.6%
3 6
 
3.6%
4 5
 
3.0%
2 5
 
3.0%
6 3
 
1.8%
7 1
 
0.6%
9 1
 
0.6%

Most occurring scripts

ValueCountFrequency (%)
Common 165
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 119
72.1%
1 12
 
7.3%
8 7
 
4.2%
5 6
 
3.6%
3 6
 
3.6%
4 5
 
3.0%
2 5
 
3.0%
6 3
 
1.8%
7 1
 
0.6%
9 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 165
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 119
72.1%
1 12
 
7.3%
8 7
 
4.2%
5 6
 
3.6%
3 6
 
3.6%
4 5
 
3.0%
2 5
 
3.0%
6 3
 
1.8%
7 1
 
0.6%
9 1
 
0.6%

q17_c11_r1
Text

MISSING 

Distinct15
Distinct (%)14.7%
Missing898
Missing (%)89.8%
Memory size34.0 KiB
2023-12-09T22:15:37.218825image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.12745098
Min length1

Characters and Unicode

Total characters115
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)8.8%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 77
75.5%
10 4
 
3.9%
2 3
 
2.9%
6 3
 
2.9%
20 3
 
2.9%
1 3
 
2.9%
7 1
 
1.0%
12 1
 
1.0%
13 1
 
1.0%
23 1
 
1.0%
Other values (5) 5
 
4.9%
2023-12-09T22:15:37.480857image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 85
73.9%
1 11
 
9.6%
2 8
 
7.0%
6 4
 
3.5%
3 4
 
3.5%
7 1
 
0.9%
5 1
 
0.9%
8 1
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 115
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 85
73.9%
1 11
 
9.6%
2 8
 
7.0%
6 4
 
3.5%
3 4
 
3.5%
7 1
 
0.9%
5 1
 
0.9%
8 1
 
0.9%

Most occurring scripts

ValueCountFrequency (%)
Common 115
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 85
73.9%
1 11
 
9.6%
2 8
 
7.0%
6 4
 
3.5%
3 4
 
3.5%
7 1
 
0.9%
5 1
 
0.9%
8 1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 115
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 85
73.9%
1 11
 
9.6%
2 8
 
7.0%
6 4
 
3.5%
3 4
 
3.5%
7 1
 
0.9%
5 1
 
0.9%
8 1
 
0.9%

q17_c11_r2
Text

MISSING 

Distinct16
Distinct (%)15.7%
Missing898
Missing (%)89.8%
Memory size34.0 KiB
2023-12-09T22:15:37.624089image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.156862745
Min length1

Characters and Unicode

Total characters118
Distinct characters9
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)7.8%

Sample

1st row0
2nd row5
3rd row2
4th row5
5th row60
ValueCountFrequency (%)
0 72
70.6%
10 4
 
3.9%
1 4
 
3.9%
2 3
 
2.9%
20 3
 
2.9%
40 3
 
2.9%
5 3
 
2.9%
8 2
 
2.0%
70 1
 
1.0%
35 1
 
1.0%
Other values (6) 6
 
5.9%
2023-12-09T22:15:37.891303image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 85
72.0%
1 9
 
7.6%
2 7
 
5.9%
5 5
 
4.2%
4 3
 
2.5%
6 3
 
2.5%
8 2
 
1.7%
7 2
 
1.7%
3 2
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 118
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 85
72.0%
1 9
 
7.6%
2 7
 
5.9%
5 5
 
4.2%
4 3
 
2.5%
6 3
 
2.5%
8 2
 
1.7%
7 2
 
1.7%
3 2
 
1.7%

Most occurring scripts

ValueCountFrequency (%)
Common 118
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 85
72.0%
1 9
 
7.6%
2 7
 
5.9%
5 5
 
4.2%
4 3
 
2.5%
6 3
 
2.5%
8 2
 
1.7%
7 2
 
1.7%
3 2
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 118
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 85
72.0%
1 9
 
7.6%
2 7
 
5.9%
5 5
 
4.2%
4 3
 
2.5%
6 3
 
2.5%
8 2
 
1.7%
7 2
 
1.7%
3 2
 
1.7%

q17_c11_r3
Text

MISSING 

Distinct12
Distinct (%)11.8%
Missing898
Missing (%)89.8%
Memory size34.0 KiB
2023-12-09T22:15:38.032232image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.088235294
Min length1

Characters and Unicode

Total characters111
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)4.9%

Sample

1st row0
2nd row0
3rd row12
4th row0
5th row0
ValueCountFrequency (%)
0 85
83.3%
7 2
 
2.0%
12 2
 
2.0%
2 2
 
2.0%
20 2
 
2.0%
10 2
 
2.0%
1 2
 
2.0%
36 1
 
1.0%
4 1
 
1.0%
16 1
 
1.0%
Other values (2) 2
 
2.0%
2023-12-09T22:15:38.286635image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 90
81.1%
1 7
 
6.3%
2 6
 
5.4%
7 2
 
1.8%
3 2
 
1.8%
6 2
 
1.8%
4 1
 
0.9%
8 1
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 111
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 90
81.1%
1 7
 
6.3%
2 6
 
5.4%
7 2
 
1.8%
3 2
 
1.8%
6 2
 
1.8%
4 1
 
0.9%
8 1
 
0.9%

Most occurring scripts

ValueCountFrequency (%)
Common 111
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 90
81.1%
1 7
 
6.3%
2 6
 
5.4%
7 2
 
1.8%
3 2
 
1.8%
6 2
 
1.8%
4 1
 
0.9%
8 1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 111
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 90
81.1%
1 7
 
6.3%
2 6
 
5.4%
7 2
 
1.8%
3 2
 
1.8%
6 2
 
1.8%
4 1
 
0.9%
8 1
 
0.9%

q17_c11_r4
Text

MISSING 

Distinct19
Distinct (%)18.6%
Missing898
Missing (%)89.8%
Memory size34.0 KiB
2023-12-09T22:15:38.431440image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.156862745
Min length1

Characters and Unicode

Total characters118
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)10.8%

Sample

1st row0
2nd row0
3rd row4
4th row0
5th row60
ValueCountFrequency (%)
0 75
73.5%
20 3
 
2.9%
8 3
 
2.9%
3 2
 
2.0%
6 2
 
2.0%
15 2
 
2.0%
1 2
 
2.0%
10 2
 
2.0%
117 1
 
1.0%
4 1
 
1.0%
Other values (9) 9
 
8.8%
2023-12-09T22:15:38.725108image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 82
69.5%
1 9
 
7.6%
2 6
 
5.1%
3 5
 
4.2%
8 4
 
3.4%
5 4
 
3.4%
6 3
 
2.5%
4 3
 
2.5%
9 1
 
0.8%
7 1
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 118
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 82
69.5%
1 9
 
7.6%
2 6
 
5.1%
3 5
 
4.2%
8 4
 
3.4%
5 4
 
3.4%
6 3
 
2.5%
4 3
 
2.5%
9 1
 
0.8%
7 1
 
0.8%

Most occurring scripts

ValueCountFrequency (%)
Common 118
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 82
69.5%
1 9
 
7.6%
2 6
 
5.1%
3 5
 
4.2%
8 4
 
3.4%
5 4
 
3.4%
6 3
 
2.5%
4 3
 
2.5%
9 1
 
0.8%
7 1
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 118
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 82
69.5%
1 9
 
7.6%
2 6
 
5.1%
3 5
 
4.2%
8 4
 
3.4%
5 4
 
3.4%
6 3
 
2.5%
4 3
 
2.5%
9 1
 
0.8%
7 1
 
0.8%

q17_c12_r1
Text

MISSING 

Distinct14
Distinct (%)17.7%
Missing921
Missing (%)92.1%
Memory size33.4 KiB
2023-12-09T22:15:38.864015image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.139240506
Min length1

Characters and Unicode

Total characters90
Distinct characters7
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)12.7%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 62
78.5%
20 3
 
3.8%
6 2
 
2.5%
10 2
 
2.5%
12 1
 
1.3%
13 1
 
1.3%
2 1
 
1.3%
23 1
 
1.3%
15 1
 
1.3%
16 1
 
1.3%
Other values (4) 4
 
5.1%
2023-12-09T22:15:39.134427image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 68
75.6%
1 7
 
7.8%
2 6
 
6.7%
3 4
 
4.4%
6 3
 
3.3%
5 1
 
1.1%
8 1
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 90
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 68
75.6%
1 7
 
7.8%
2 6
 
6.7%
3 4
 
4.4%
6 3
 
3.3%
5 1
 
1.1%
8 1
 
1.1%

Most occurring scripts

ValueCountFrequency (%)
Common 90
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 68
75.6%
1 7
 
7.8%
2 6
 
6.7%
3 4
 
4.4%
6 3
 
3.3%
5 1
 
1.1%
8 1
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 90
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 68
75.6%
1 7
 
7.8%
2 6
 
6.7%
3 4
 
4.4%
6 3
 
3.3%
5 1
 
1.1%
8 1
 
1.1%

q17_c12_r2
Text

MISSING 

Distinct16
Distinct (%)20.3%
Missing921
Missing (%)92.1%
Memory size33.4 KiB
2023-12-09T22:15:39.271780image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.17721519
Min length1

Characters and Unicode

Total characters93
Distinct characters9
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)12.7%

Sample

1st row0
2nd row5
3rd row2
4th row5
5th row60
ValueCountFrequency (%)
0 54
68.4%
1 5
 
6.3%
10 3
 
3.8%
5 3
 
3.8%
40 2
 
2.5%
20 2
 
2.5%
70 1
 
1.3%
35 1
 
1.3%
30 1
 
1.3%
12 1
 
1.3%
Other values (6) 6
 
7.6%
2023-12-09T22:15:39.530332image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 64
68.8%
1 10
 
10.8%
5 5
 
5.4%
2 5
 
5.4%
6 3
 
3.2%
4 2
 
2.2%
3 2
 
2.2%
7 1
 
1.1%
8 1
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 93
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 64
68.8%
1 10
 
10.8%
5 5
 
5.4%
2 5
 
5.4%
6 3
 
3.2%
4 2
 
2.2%
3 2
 
2.2%
7 1
 
1.1%
8 1
 
1.1%

Most occurring scripts

ValueCountFrequency (%)
Common 93
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 64
68.8%
1 10
 
10.8%
5 5
 
5.4%
2 5
 
5.4%
6 3
 
3.2%
4 2
 
2.2%
3 2
 
2.2%
7 1
 
1.1%
8 1
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 93
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 64
68.8%
1 10
 
10.8%
5 5
 
5.4%
2 5
 
5.4%
6 3
 
3.2%
4 2
 
2.2%
3 2
 
2.2%
7 1
 
1.1%
8 1
 
1.1%

q17_c12_r3
Text

MISSING 

Distinct10
Distinct (%)12.7%
Missing921
Missing (%)92.1%
Memory size33.4 KiB
2023-12-09T22:15:39.658095image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.113924051
Min length1

Characters and Unicode

Total characters88
Distinct characters7
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)6.3%

Sample

1st row0
2nd row0
3rd row12
4th row0
5th row0
ValueCountFrequency (%)
0 66
83.5%
12 2
 
2.5%
20 2
 
2.5%
10 2
 
2.5%
1 2
 
2.5%
36 1
 
1.3%
9 1
 
1.3%
4 1
 
1.3%
16 1
 
1.3%
30 1
 
1.3%
2023-12-09T22:15:39.905840image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 71
80.7%
1 7
 
8.0%
2 4
 
4.5%
3 2
 
2.3%
6 2
 
2.3%
9 1
 
1.1%
4 1
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 88
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 71
80.7%
1 7
 
8.0%
2 4
 
4.5%
3 2
 
2.3%
6 2
 
2.3%
9 1
 
1.1%
4 1
 
1.1%

Most occurring scripts

ValueCountFrequency (%)
Common 88
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 71
80.7%
1 7
 
8.0%
2 4
 
4.5%
3 2
 
2.3%
6 2
 
2.3%
9 1
 
1.1%
4 1
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 88
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 71
80.7%
1 7
 
8.0%
2 4
 
4.5%
3 2
 
2.3%
6 2
 
2.3%
9 1
 
1.1%
4 1
 
1.1%

q17_c12_r4
Text

MISSING 

Distinct17
Distinct (%)21.5%
Missing921
Missing (%)92.1%
Memory size33.4 KiB
2023-12-09T22:15:40.048775image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.17721519
Min length1

Characters and Unicode

Total characters93
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)13.9%

Sample

1st row0
2nd row0
3rd row4
4th row0
5th row60
ValueCountFrequency (%)
0 56
70.9%
20 3
 
3.8%
6 3
 
3.8%
1 2
 
2.5%
15 2
 
2.5%
8 2
 
2.5%
10 1
 
1.3%
12 1
 
1.3%
9 1
 
1.3%
4 1
 
1.3%
Other values (7) 7
 
8.9%
2023-12-09T22:15:40.336028image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 62
66.7%
1 9
 
9.7%
2 5
 
5.4%
6 4
 
4.3%
5 4
 
4.3%
8 3
 
3.2%
3 2
 
2.2%
4 2
 
2.2%
7 1
 
1.1%
9 1
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 93
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 62
66.7%
1 9
 
9.7%
2 5
 
5.4%
6 4
 
4.3%
5 4
 
4.3%
8 3
 
3.2%
3 2
 
2.2%
4 2
 
2.2%
7 1
 
1.1%
9 1
 
1.1%

Most occurring scripts

ValueCountFrequency (%)
Common 93
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 62
66.7%
1 9
 
9.7%
2 5
 
5.4%
6 4
 
4.3%
5 4
 
4.3%
8 3
 
3.2%
3 2
 
2.2%
4 2
 
2.2%
7 1
 
1.1%
9 1
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 93
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 62
66.7%
1 9
 
9.7%
2 5
 
5.4%
6 4
 
4.3%
5 4
 
4.3%
8 3
 
3.2%
3 2
 
2.2%
4 2
 
2.2%
7 1
 
1.1%
9 1
 
1.1%

q17_c13_r1
Text

MISSING 

Distinct11
Distinct (%)17.7%
Missing938
Missing (%)93.8%
Memory size33.0 KiB
2023-12-09T22:15:40.463923image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.177419355
Min length1

Characters and Unicode

Total characters73
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)11.3%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 47
75.8%
20 4
 
6.5%
12 2
 
3.2%
10 2
 
3.2%
2 1
 
1.6%
6 1
 
1.6%
23 1
 
1.6%
15 1
 
1.6%
16 1
 
1.6%
3 1
 
1.6%
2023-12-09T22:15:40.712787image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 53
72.6%
2 8
 
11.0%
1 7
 
9.6%
6 2
 
2.7%
3 2
 
2.7%
5 1
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 73
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 53
72.6%
2 8
 
11.0%
1 7
 
9.6%
6 2
 
2.7%
3 2
 
2.7%
5 1
 
1.4%

Most occurring scripts

ValueCountFrequency (%)
Common 73
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 53
72.6%
2 8
 
11.0%
1 7
 
9.6%
6 2
 
2.7%
3 2
 
2.7%
5 1
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 73
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 53
72.6%
2 8
 
11.0%
1 7
 
9.6%
6 2
 
2.7%
3 2
 
2.7%
5 1
 
1.4%

q17_c13_r2
Text

MISSING 

Distinct12
Distinct (%)19.4%
Missing938
Missing (%)93.8%
Memory size33.0 KiB
2023-12-09T22:15:40.841906image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.14516129
Min length1

Characters and Unicode

Total characters71
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)12.9%

Sample

1st row0
2nd row5
3rd row60
4th row1
5th row0
ValueCountFrequency (%)
0 46
74.2%
1 4
 
6.5%
20 2
 
3.2%
5 2
 
3.2%
12 1
 
1.6%
16 1
 
1.6%
8 1
 
1.6%
30 1
 
1.6%
10 1
 
1.6%
35 1
 
1.6%
Other values (2) 2
 
3.2%
2023-12-09T22:15:41.095814image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 52
73.2%
1 7
 
9.9%
2 3
 
4.2%
5 3
 
4.2%
6 2
 
2.8%
3 2
 
2.8%
8 1
 
1.4%
7 1
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 71
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 52
73.2%
1 7
 
9.9%
2 3
 
4.2%
5 3
 
4.2%
6 2
 
2.8%
3 2
 
2.8%
8 1
 
1.4%
7 1
 
1.4%

Most occurring scripts

ValueCountFrequency (%)
Common 71
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 52
73.2%
1 7
 
9.9%
2 3
 
4.2%
5 3
 
4.2%
6 2
 
2.8%
3 2
 
2.8%
8 1
 
1.4%
7 1
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 71
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 52
73.2%
1 7
 
9.9%
2 3
 
4.2%
5 3
 
4.2%
6 2
 
2.8%
3 2
 
2.8%
8 1
 
1.4%
7 1
 
1.4%

q17_c13_r3
Text

MISSING 

Distinct6
Distinct (%)9.7%
Missing938
Missing (%)93.8%
Memory size33.0 KiB
2023-12-09T22:15:41.214736image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.080645161
Min length1

Characters and Unicode

Total characters67
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)4.8%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 55
88.7%
12 2
 
3.2%
1 2
 
3.2%
36 1
 
1.6%
20 1
 
1.6%
30 1
 
1.6%
2023-12-09T22:15:41.461845image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 57
85.1%
1 4
 
6.0%
2 3
 
4.5%
3 2
 
3.0%
6 1
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 67
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 57
85.1%
1 4
 
6.0%
2 3
 
4.5%
3 2
 
3.0%
6 1
 
1.5%

Most occurring scripts

ValueCountFrequency (%)
Common 67
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 57
85.1%
1 4
 
6.0%
2 3
 
4.5%
3 2
 
3.0%
6 1
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 67
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 57
85.1%
1 4
 
6.0%
2 3
 
4.5%
3 2
 
3.0%
6 1
 
1.5%

q17_c13_r4
Text

MISSING 

Distinct15
Distinct (%)24.2%
Missing938
Missing (%)93.8%
Memory size33.0 KiB
2023-12-09T22:15:41.605988image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.209677419
Min length1

Characters and Unicode

Total characters75
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)16.1%

Sample

1st row0
2nd row0
3rd row60
4th row0
5th row0
ValueCountFrequency (%)
0 44
71.0%
12 2
 
3.2%
6 2
 
3.2%
20 2
 
3.2%
1 2
 
3.2%
25 1
 
1.6%
15 1
 
1.6%
17 1
 
1.6%
8 1
 
1.6%
18 1
 
1.6%
Other values (5) 5
 
8.1%
2023-12-09T22:15:41.886574image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 48
64.0%
1 10
 
13.3%
2 5
 
6.7%
6 3
 
4.0%
5 3
 
4.0%
7 2
 
2.7%
8 2
 
2.7%
3 2
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 75
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 48
64.0%
1 10
 
13.3%
2 5
 
6.7%
6 3
 
4.0%
5 3
 
4.0%
7 2
 
2.7%
8 2
 
2.7%
3 2
 
2.7%

Most occurring scripts

ValueCountFrequency (%)
Common 75
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 48
64.0%
1 10
 
13.3%
2 5
 
6.7%
6 3
 
4.0%
5 3
 
4.0%
7 2
 
2.7%
8 2
 
2.7%
3 2
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 75
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 48
64.0%
1 10
 
13.3%
2 5
 
6.7%
6 3
 
4.0%
5 3
 
4.0%
7 2
 
2.7%
8 2
 
2.7%
3 2
 
2.7%

q17_c14_r1
Text

MISSING 

Distinct7
Distinct (%)14.3%
Missing951
Missing (%)95.1%
Memory size32.6 KiB
2023-12-09T22:15:42.012937image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.163265306
Min length1

Characters and Unicode

Total characters57
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)8.2%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 40
81.6%
20 3
 
6.1%
10 2
 
4.1%
12 1
 
2.0%
6 1
 
2.0%
23 1
 
2.0%
16 1
 
2.0%
2023-12-09T22:15:42.252079image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 45
78.9%
2 5
 
8.8%
1 4
 
7.0%
6 2
 
3.5%
3 1
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 57
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 45
78.9%
2 5
 
8.8%
1 4
 
7.0%
6 2
 
3.5%
3 1
 
1.8%

Most occurring scripts

ValueCountFrequency (%)
Common 57
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 45
78.9%
2 5
 
8.8%
1 4
 
7.0%
6 2
 
3.5%
3 1
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 57
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 45
78.9%
2 5
 
8.8%
1 4
 
7.0%
6 2
 
3.5%
3 1
 
1.8%

q17_c14_r2
Text

MISSING 

Distinct11
Distinct (%)22.4%
Missing951
Missing (%)95.1%
Memory size32.6 KiB
2023-12-09T22:15:42.382169image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.163265306
Min length1

Characters and Unicode

Total characters57
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)16.3%

Sample

1st row0
2nd row5
3rd row1
4th row0
5th row0
ValueCountFrequency (%)
0 37
75.5%
20 2
 
4.1%
1 2
 
4.1%
12 1
 
2.0%
16 1
 
2.0%
8 1
 
2.0%
30 1
 
2.0%
5 1
 
2.0%
10 1
 
2.0%
35 1
 
2.0%
2023-12-09T22:15:42.631736image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 42
73.7%
1 5
 
8.8%
2 3
 
5.3%
3 2
 
3.5%
5 2
 
3.5%
6 1
 
1.8%
8 1
 
1.8%
7 1
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 57
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 42
73.7%
1 5
 
8.8%
2 3
 
5.3%
3 2
 
3.5%
5 2
 
3.5%
6 1
 
1.8%
8 1
 
1.8%
7 1
 
1.8%

Most occurring scripts

ValueCountFrequency (%)
Common 57
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 42
73.7%
1 5
 
8.8%
2 3
 
5.3%
3 2
 
3.5%
5 2
 
3.5%
6 1
 
1.8%
8 1
 
1.8%
7 1
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 57
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 42
73.7%
1 5
 
8.8%
2 3
 
5.3%
3 2
 
3.5%
5 2
 
3.5%
6 1
 
1.8%
8 1
 
1.8%
7 1
 
1.8%

q17_c14_r3
Text

MISSING 

Distinct6
Distinct (%)12.2%
Missing951
Missing (%)95.1%
Memory size32.6 KiB
2023-12-09T22:15:42.763318image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.081632653
Min length1

Characters and Unicode

Total characters53
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)10.2%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 44
89.8%
36 1
 
2.0%
12 1
 
2.0%
20 1
 
2.0%
30 1
 
2.0%
1 1
 
2.0%
2023-12-09T22:15:43.007485image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 46
86.8%
3 2
 
3.8%
1 2
 
3.8%
2 2
 
3.8%
6 1
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 53
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 46
86.8%
3 2
 
3.8%
1 2
 
3.8%
2 2
 
3.8%
6 1
 
1.9%

Most occurring scripts

ValueCountFrequency (%)
Common 53
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 46
86.8%
3 2
 
3.8%
1 2
 
3.8%
2 2
 
3.8%
6 1
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 53
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 46
86.8%
3 2
 
3.8%
1 2
 
3.8%
2 2
 
3.8%
6 1
 
1.9%

q17_c14_r4
Text

MISSING 

Distinct12
Distinct (%)24.5%
Missing951
Missing (%)95.1%
Memory size32.6 KiB
2023-12-09T22:15:43.146132image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.183673469
Min length1

Characters and Unicode

Total characters58
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)18.4%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 36
73.5%
6 2
 
4.1%
20 2
 
4.1%
25 1
 
2.0%
12 1
 
2.0%
2 1
 
2.0%
11 1
 
2.0%
8 1
 
2.0%
18 1
 
2.0%
117 1
 
2.0%
Other values (2) 2
 
4.1%
2023-12-09T22:15:43.424384image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 38
65.5%
1 7
 
12.1%
2 5
 
8.6%
6 2
 
3.4%
5 2
 
3.4%
8 2
 
3.4%
7 1
 
1.7%
3 1
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 58
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 38
65.5%
1 7
 
12.1%
2 5
 
8.6%
6 2
 
3.4%
5 2
 
3.4%
8 2
 
3.4%
7 1
 
1.7%
3 1
 
1.7%

Most occurring scripts

ValueCountFrequency (%)
Common 58
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 38
65.5%
1 7
 
12.1%
2 5
 
8.6%
6 2
 
3.4%
5 2
 
3.4%
8 2
 
3.4%
7 1
 
1.7%
3 1
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 58
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 38
65.5%
1 7
 
12.1%
2 5
 
8.6%
6 2
 
3.4%
5 2
 
3.4%
8 2
 
3.4%
7 1
 
1.7%
3 1
 
1.7%

q17_c15_r1
Text

MISSING 

Distinct7
Distinct (%)17.1%
Missing959
Missing (%)95.9%
Memory size32.4 KiB
2023-12-09T22:15:43.550776image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.170731707
Min length1

Characters and Unicode

Total characters48
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)12.2%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 33
80.5%
20 3
 
7.3%
12 1
 
2.4%
6 1
 
2.4%
23 1
 
2.4%
16 1
 
2.4%
10 1
 
2.4%
2023-12-09T22:15:43.808413image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 37
77.1%
2 5
 
10.4%
1 3
 
6.2%
6 2
 
4.2%
3 1
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 48
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 37
77.1%
2 5
 
10.4%
1 3
 
6.2%
6 2
 
4.2%
3 1
 
2.1%

Most occurring scripts

ValueCountFrequency (%)
Common 48
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 37
77.1%
2 5
 
10.4%
1 3
 
6.2%
6 2
 
4.2%
3 1
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 48
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 37
77.1%
2 5
 
10.4%
1 3
 
6.2%
6 2
 
4.2%
3 1
 
2.1%

q17_c15_r2
Text

MISSING 

Distinct10
Distinct (%)24.4%
Missing959
Missing (%)95.9%
Memory size32.4 KiB
2023-12-09T22:15:43.937914image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.170731707
Min length1

Characters and Unicode

Total characters48
Distinct characters7
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)17.1%

Sample

1st row0
2nd row5
3rd row1
4th row0
5th row0
ValueCountFrequency (%)
0 30
73.2%
20 2
 
4.9%
1 2
 
4.9%
12 1
 
2.4%
8 1
 
2.4%
30 1
 
2.4%
5 1
 
2.4%
10 1
 
2.4%
35 1
 
2.4%
70 1
 
2.4%
2023-12-09T22:15:44.207002image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 35
72.9%
1 4
 
8.3%
2 3
 
6.2%
3 2
 
4.2%
5 2
 
4.2%
8 1
 
2.1%
7 1
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 48
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 35
72.9%
1 4
 
8.3%
2 3
 
6.2%
3 2
 
4.2%
5 2
 
4.2%
8 1
 
2.1%
7 1
 
2.1%

Most occurring scripts

ValueCountFrequency (%)
Common 48
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 35
72.9%
1 4
 
8.3%
2 3
 
6.2%
3 2
 
4.2%
5 2
 
4.2%
8 1
 
2.1%
7 1
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 48
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 35
72.9%
1 4
 
8.3%
2 3
 
6.2%
3 2
 
4.2%
5 2
 
4.2%
8 1
 
2.1%
7 1
 
2.1%

q17_c15_r3
Text

MISSING 

Distinct7
Distinct (%)17.1%
Missing959
Missing (%)95.9%
Memory size32.4 KiB
2023-12-09T22:15:44.336531image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.097560976
Min length1

Characters and Unicode

Total characters45
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)14.6%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 35
85.4%
36 1
 
2.4%
12 1
 
2.4%
9 1
 
2.4%
20 1
 
2.4%
30 1
 
2.4%
1 1
 
2.4%
2023-12-09T22:15:44.580176image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 37
82.2%
3 2
 
4.4%
1 2
 
4.4%
2 2
 
4.4%
6 1
 
2.2%
9 1
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 45
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 37
82.2%
3 2
 
4.4%
1 2
 
4.4%
2 2
 
4.4%
6 1
 
2.2%
9 1
 
2.2%

Most occurring scripts

ValueCountFrequency (%)
Common 45
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 37
82.2%
3 2
 
4.4%
1 2
 
4.4%
2 2
 
4.4%
6 1
 
2.2%
9 1
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 45
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 37
82.2%
3 2
 
4.4%
1 2
 
4.4%
2 2
 
4.4%
6 1
 
2.2%
9 1
 
2.2%

q17_c15_r4
Text

MISSING 

Distinct8
Distinct (%)19.5%
Missing959
Missing (%)95.9%
Memory size32.4 KiB
2023-12-09T22:15:44.700118image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.146341463
Min length1

Characters and Unicode

Total characters47
Distinct characters7
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)12.2%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 32
78.0%
6 2
 
4.9%
20 2
 
4.9%
25 1
 
2.4%
12 1
 
2.4%
8 1
 
2.4%
18 1
 
2.4%
35 1
 
2.4%
2023-12-09T22:15:44.941953image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 34
72.3%
2 4
 
8.5%
6 2
 
4.3%
5 2
 
4.3%
1 2
 
4.3%
8 2
 
4.3%
3 1
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 47
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 34
72.3%
2 4
 
8.5%
6 2
 
4.3%
5 2
 
4.3%
1 2
 
4.3%
8 2
 
4.3%
3 1
 
2.1%

Most occurring scripts

ValueCountFrequency (%)
Common 47
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 34
72.3%
2 4
 
8.5%
6 2
 
4.3%
5 2
 
4.3%
1 2
 
4.3%
8 2
 
4.3%
3 1
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 47
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 34
72.3%
2 4
 
8.5%
6 2
 
4.3%
5 2
 
4.3%
1 2
 
4.3%
8 2
 
4.3%
3 1
 
2.1%

q17_c16_r1
Text

MISSING 

Distinct6
Distinct (%)20.0%
Missing970
Missing (%)97.0%
Memory size32.1 KiB
2023-12-09T22:15:45.061260image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.2
Min length1

Characters and Unicode

Total characters36
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)13.3%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 23
76.7%
20 3
 
10.0%
12 1
 
3.3%
6 1
 
3.3%
23 1
 
3.3%
16 1
 
3.3%
2023-12-09T22:15:45.302182image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 26
72.2%
2 5
 
13.9%
1 2
 
5.6%
6 2
 
5.6%
3 1
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 36
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 26
72.2%
2 5
 
13.9%
1 2
 
5.6%
6 2
 
5.6%
3 1
 
2.8%

Most occurring scripts

ValueCountFrequency (%)
Common 36
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 26
72.2%
2 5
 
13.9%
1 2
 
5.6%
6 2
 
5.6%
3 1
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 36
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 26
72.2%
2 5
 
13.9%
1 2
 
5.6%
6 2
 
5.6%
3 1
 
2.8%

q17_c16_r2
Text

MISSING 

Distinct8
Distinct (%)26.7%
Missing970
Missing (%)97.0%
Memory size32.1 KiB
2023-12-09T22:15:45.419252image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.2
Min length1

Characters and Unicode

Total characters36
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)20.0%

Sample

1st row0
2nd row5
3rd row1
4th row0
5th row0
ValueCountFrequency (%)
0 22
73.3%
20 2
 
6.7%
12 1
 
3.3%
30 1
 
3.3%
5 1
 
3.3%
10 1
 
3.3%
1 1
 
3.3%
70 1
 
3.3%
2023-12-09T22:15:45.657513image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 27
75.0%
2 3
 
8.3%
1 3
 
8.3%
3 1
 
2.8%
5 1
 
2.8%
7 1
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 36
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 27
75.0%
2 3
 
8.3%
1 3
 
8.3%
3 1
 
2.8%
5 1
 
2.8%
7 1
 
2.8%

Most occurring scripts

ValueCountFrequency (%)
Common 36
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 27
75.0%
2 3
 
8.3%
1 3
 
8.3%
3 1
 
2.8%
5 1
 
2.8%
7 1
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 36
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 27
75.0%
2 3
 
8.3%
1 3
 
8.3%
3 1
 
2.8%
5 1
 
2.8%
7 1
 
2.8%

q17_c16_r3
Text

MISSING 

Distinct6
Distinct (%)20.0%
Missing970
Missing (%)97.0%
Memory size32.1 KiB
2023-12-09T22:15:45.774282image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.133333333
Min length1

Characters and Unicode

Total characters34
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)16.7%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 25
83.3%
36 1
 
3.3%
7 1
 
3.3%
12 1
 
3.3%
20 1
 
3.3%
30 1
 
3.3%
2023-12-09T22:15:46.016904image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 27
79.4%
3 2
 
5.9%
2 2
 
5.9%
6 1
 
2.9%
7 1
 
2.9%
1 1
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 34
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 27
79.4%
3 2
 
5.9%
2 2
 
5.9%
6 1
 
2.9%
7 1
 
2.9%
1 1
 
2.9%

Most occurring scripts

ValueCountFrequency (%)
Common 34
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 27
79.4%
3 2
 
5.9%
2 2
 
5.9%
6 1
 
2.9%
7 1
 
2.9%
1 1
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 34
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 27
79.4%
3 2
 
5.9%
2 2
 
5.9%
6 1
 
2.9%
7 1
 
2.9%
1 1
 
2.9%

q17_c16_r4
Text

MISSING 

Distinct6
Distinct (%)20.0%
Missing970
Missing (%)97.0%
Memory size32.1 KiB
2023-12-09T22:15:46.135246image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.133333333
Min length1

Characters and Unicode

Total characters34
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)13.3%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 24
80.0%
6 2
 
6.7%
25 1
 
3.3%
12 1
 
3.3%
20 1
 
3.3%
18 1
 
3.3%
2023-12-09T22:15:46.374101image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 25
73.5%
2 3
 
8.8%
6 2
 
5.9%
1 2
 
5.9%
5 1
 
2.9%
8 1
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 34
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 25
73.5%
2 3
 
8.8%
6 2
 
5.9%
1 2
 
5.9%
5 1
 
2.9%
8 1
 
2.9%

Most occurring scripts

ValueCountFrequency (%)
Common 34
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 25
73.5%
2 3
 
8.8%
6 2
 
5.9%
1 2
 
5.9%
5 1
 
2.9%
8 1
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 34
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 25
73.5%
2 3
 
8.8%
6 2
 
5.9%
1 2
 
5.9%
5 1
 
2.9%
8 1
 
2.9%

q23_r7_c1
Text

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size56.8 KiB
2023-12-09T22:15:46.479287image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 1000
100.0%
2023-12-09T22:15:46.691232image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1000
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1000
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1000
100.0%

q23_r7_c2
Text

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size56.8 KiB
2023-12-09T22:15:46.793707image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 1000
100.0%
2023-12-09T22:15:47.011428image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1000
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1000
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1000
100.0%

q23_r7_c3
Text

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size56.8 KiB
2023-12-09T22:15:47.118409image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 1000
100.0%
2023-12-09T22:15:47.336872image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1000
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1000
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1000
100.0%

q23_r7_c4
Text

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size56.8 KiB
2023-12-09T22:15:47.441012image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 1000
100.0%
2023-12-09T22:15:47.667319image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1000
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1000
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1000
100.0%

q24_1
Text

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size56.8 KiB
2023-12-09T22:15:47.775052image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row1
5th row0
ValueCountFrequency (%)
0 946
94.6%
1 54
 
5.4%
2023-12-09T22:15:48.015196image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 946
94.6%
1 54
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 946
94.6%
1 54
 
5.4%

Most occurring scripts

ValueCountFrequency (%)
Common 1000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 946
94.6%
1 54
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 946
94.6%
1 54
 
5.4%

q24_2
Text

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size56.8 KiB
2023-12-09T22:15:48.127895image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row1
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 941
94.1%
1 59
 
5.9%
2023-12-09T22:15:48.351813image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 941
94.1%
1 59
 
5.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 941
94.1%
1 59
 
5.9%

Most occurring scripts

ValueCountFrequency (%)
Common 1000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 941
94.1%
1 59
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 941
94.1%
1 59
 
5.9%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size56.8 KiB
2023-12-09T22:15:48.464809image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 989
98.9%
1 11
 
1.1%
2023-12-09T22:15:48.698882image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 989
98.9%
1 11
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 989
98.9%
1 11
 
1.1%

Most occurring scripts

ValueCountFrequency (%)
Common 1000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 989
98.9%
1 11
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 989
98.9%
1 11
 
1.1%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size56.8 KiB
2023-12-09T22:15:48.807197image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 976
97.6%
1 24
 
2.4%
2023-12-09T22:15:49.047868image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 976
97.6%
1 24
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 976
97.6%
1 24
 
2.4%

Most occurring scripts

ValueCountFrequency (%)
Common 1000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 976
97.6%
1 24
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 976
97.6%
1 24
 
2.4%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size56.8 KiB
2023-12-09T22:15:49.164539image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 992
99.2%
1 8
 
0.8%
2023-12-09T22:15:50.304926image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 992
99.2%
1 8
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 992
99.2%
1 8
 
0.8%

Most occurring scripts

ValueCountFrequency (%)
Common 1000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 992
99.2%
1 8
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 992
99.2%
1 8
 
0.8%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size56.8 KiB
2023-12-09T22:15:50.416073image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row1
5th row0
ValueCountFrequency (%)
0 961
96.1%
1 39
 
3.9%
2023-12-09T22:15:50.650664image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 961
96.1%
1 39
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 961
96.1%
1 39
 
3.9%

Most occurring scripts

ValueCountFrequency (%)
Common 1000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 961
96.1%
1 39
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 961
96.1%
1 39
 
3.9%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size56.8 KiB
2023-12-09T22:15:50.758129image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 998
99.8%
1 2
 
0.2%
2023-12-09T22:15:50.981577image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 998
99.8%
1 2
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 998
99.8%
1 2
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Common 1000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 998
99.8%
1 2
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 998
99.8%
1 2
 
0.2%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size56.8 KiB
2023-12-09T22:15:51.090382image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 982
98.2%
1 18
 
1.8%
2023-12-09T22:15:51.311228image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 982
98.2%
1 18
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 982
98.2%
1 18
 
1.8%

Most occurring scripts

ValueCountFrequency (%)
Common 1000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 982
98.2%
1 18
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 982
98.2%
1 18
 
1.8%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size56.8 KiB
2023-12-09T22:15:51.433086image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 985
98.5%
1 15
 
1.5%
2023-12-09T22:15:51.654603image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 985
98.5%
1 15
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 985
98.5%
1 15
 
1.5%

Most occurring scripts

ValueCountFrequency (%)
Common 1000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 985
98.5%
1 15
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 985
98.5%
1 15
 
1.5%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size56.8 KiB
2023-12-09T22:15:51.764189image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 995
99.5%
1 5
 
0.5%
2023-12-09T22:15:52.045479image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 995
99.5%
1 5
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 995
99.5%
1 5
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
Common 1000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 995
99.5%
1 5
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 995
99.5%
1 5
 
0.5%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size56.8 KiB
2023-12-09T22:15:52.153501image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row1
5th row0
ValueCountFrequency (%)
0 972
97.2%
1 28
 
2.8%
2023-12-09T22:15:52.429533image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 972
97.2%
1 28
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 972
97.2%
1 28
 
2.8%

Most occurring scripts

ValueCountFrequency (%)
Common 1000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 972
97.2%
1 28
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 972
97.2%
1 28
 
2.8%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size56.8 KiB
2023-12-09T22:15:52.552196image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 995
99.5%
1 5
 
0.5%
2023-12-09T22:15:52.812257image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 995
99.5%
1 5
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 995
99.5%
1 5
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
Common 1000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 995
99.5%
1 5
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 995
99.5%
1 5
 
0.5%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size56.8 KiB
2023-12-09T22:15:52.920469image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row1
5th row0
ValueCountFrequency (%)
0 979
97.9%
1 21
 
2.1%
2023-12-09T22:15:53.154923image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 979
97.9%
1 21
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 979
97.9%
1 21
 
2.1%

Most occurring scripts

ValueCountFrequency (%)
Common 1000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 979
97.9%
1 21
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 979
97.9%
1 21
 
2.1%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size56.8 KiB
2023-12-09T22:15:53.264224image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row1
5th row0
ValueCountFrequency (%)
0 977
97.7%
1 23
 
2.3%
2023-12-09T22:15:53.499053image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 977
97.7%
1 23
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 977
97.7%
1 23
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
Common 1000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 977
97.7%
1 23
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 977
97.7%
1 23
 
2.3%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size56.8 KiB
2023-12-09T22:15:53.607549image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row1
5th row0
ValueCountFrequency (%)
0 989
98.9%
1 11
 
1.1%
2023-12-09T22:15:53.855603image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 989
98.9%
1 11
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 989
98.9%
1 11
 
1.1%

Most occurring scripts

ValueCountFrequency (%)
Common 1000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 989
98.9%
1 11
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 989
98.9%
1 11
 
1.1%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size56.8 KiB
2023-12-09T22:15:53.970963image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row1
5th row0
ValueCountFrequency (%)
0 959
95.9%
1 41
 
4.1%
2023-12-09T22:15:54.198470image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 959
95.9%
1 41
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 959
95.9%
1 41
 
4.1%

Most occurring scripts

ValueCountFrequency (%)
Common 1000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 959
95.9%
1 41
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 959
95.9%
1 41
 
4.1%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size56.8 KiB
2023-12-09T22:15:54.305240image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 998
99.8%
1 2
 
0.2%
2023-12-09T22:15:54.525975image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 998
99.8%
1 2
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 998
99.8%
1 2
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Common 1000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 998
99.8%
1 2
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 998
99.8%
1 2
 
0.2%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size56.8 KiB
2023-12-09T22:15:54.633672image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 984
98.4%
1 16
 
1.6%
2023-12-09T22:15:54.862848image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 984
98.4%
1 16
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 984
98.4%
1 16
 
1.6%

Most occurring scripts

ValueCountFrequency (%)
Common 1000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 984
98.4%
1 16
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 984
98.4%
1 16
 
1.6%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size56.8 KiB
2023-12-09T22:15:54.971456image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 987
98.7%
1 13
 
1.3%
2023-12-09T22:15:55.218327image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 987
98.7%
1 13
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 987
98.7%
1 13
 
1.3%

Most occurring scripts

ValueCountFrequency (%)
Common 1000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 987
98.7%
1 13
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 987
98.7%
1 13
 
1.3%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size56.8 KiB
2023-12-09T22:15:55.334441image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 995
99.5%
1 5
 
0.5%
2023-12-09T22:15:55.557001image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 995
99.5%
1 5
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 995
99.5%
1 5
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
Common 1000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 995
99.5%
1 5
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 995
99.5%
1 5
 
0.5%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size56.8 KiB
2023-12-09T22:15:55.663849image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row1
5th row0
ValueCountFrequency (%)
0 989
98.9%
1 11
 
1.1%
2023-12-09T22:15:55.889717image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 989
98.9%
1 11
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 989
98.9%
1 11
 
1.1%

Most occurring scripts

ValueCountFrequency (%)
Common 1000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 989
98.9%
1 11
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 989
98.9%
1 11
 
1.1%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size56.8 KiB
2023-12-09T22:15:56.005141image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 991
99.1%
1 9
 
0.9%
2023-12-09T22:15:56.254515image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 991
99.1%
1 9
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 991
99.1%
1 9
 
0.9%

Most occurring scripts

ValueCountFrequency (%)
Common 1000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 991
99.1%
1 9
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 991
99.1%
1 9
 
0.9%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size56.8 KiB
2023-12-09T22:15:56.366164image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 995
99.5%
1 5
 
0.5%
2023-12-09T22:15:56.602693image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 995
99.5%
1 5
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 995
99.5%
1 5
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
Common 1000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 995
99.5%
1 5
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 995
99.5%
1 5
 
0.5%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size56.8 KiB
2023-12-09T22:15:56.717627image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 990
99.0%
1 10
 
1.0%
2023-12-09T22:15:57.009232image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 990
99.0%
1 10
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 990
99.0%
1 10
 
1.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 990
99.0%
1 10
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 990
99.0%
1 10
 
1.0%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size56.8 KiB
2023-12-09T22:15:57.121108image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 994
99.4%
1 6
 
0.6%
2023-12-09T22:15:57.405273image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 994
99.4%
1 6
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 994
99.4%
1 6
 
0.6%

Most occurring scripts

ValueCountFrequency (%)
Common 1000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 994
99.4%
1 6
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 994
99.4%
1 6
 
0.6%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size56.8 KiB
2023-12-09T22:15:57.515339image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row1
5th row0
ValueCountFrequency (%)
0 970
97.0%
1 30
 
3.0%
2023-12-09T22:15:57.732951image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 970
97.0%
1 30
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 970
97.0%
1 30
 
3.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 970
97.0%
1 30
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 970
97.0%
1 30
 
3.0%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size56.8 KiB
2023-12-09T22:15:57.840049image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 994
99.4%
1 6
 
0.6%
2023-12-09T22:15:58.069021image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 994
99.4%
1 6
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 994
99.4%
1 6
 
0.6%

Most occurring scripts

ValueCountFrequency (%)
Common 1000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 994
99.4%
1 6
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 994
99.4%
1 6
 
0.6%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size56.8 KiB
2023-12-09T22:15:58.181988image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 994
99.4%
1 6
 
0.6%
2023-12-09T22:15:58.412151image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 994
99.4%
1 6
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 994
99.4%
1 6
 
0.6%

Most occurring scripts

ValueCountFrequency (%)
Common 1000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 994
99.4%
1 6
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 994
99.4%
1 6
 
0.6%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size56.8 KiB
2023-12-09T22:15:58.520291image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 981
98.1%
1 19
 
1.9%
2023-12-09T22:15:58.735486image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 981
98.1%
1 19
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 981
98.1%
1 19
 
1.9%

Most occurring scripts

ValueCountFrequency (%)
Common 1000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 981
98.1%
1 19
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 981
98.1%
1 19
 
1.9%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size56.8 KiB
2023-12-09T22:15:58.840121image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 990
99.0%
1 10
 
1.0%
2023-12-09T22:15:59.058841image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 990
99.0%
1 10
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 990
99.0%
1 10
 
1.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 990
99.0%
1 10
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 990
99.0%
1 10
 
1.0%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size56.8 KiB
2023-12-09T22:15:59.164611image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row1
5th row0
ValueCountFrequency (%)
0 961
96.1%
1 39
 
3.9%
2023-12-09T22:15:59.381319image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 961
96.1%
1 39
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 961
96.1%
1 39
 
3.9%

Most occurring scripts

ValueCountFrequency (%)
Common 1000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 961
96.1%
1 39
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 961
96.1%
1 39
 
3.9%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size56.8 KiB
2023-12-09T22:15:59.487101image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 998
99.8%
1 2
 
0.2%
2023-12-09T22:15:59.702113image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 998
99.8%
1 2
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 998
99.8%
1 2
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Common 1000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 998
99.8%
1 2
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 998
99.8%
1 2
 
0.2%

q26_1
Text

MISSING 

Distinct7
Distinct (%)0.8%
Missing111
Missing (%)11.1%
Memory size53.9 KiB
2023-12-09T22:15:59.815300image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters889
Distinct characters7
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)0.3%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 703
79.1%
1 166
 
18.7%
2 14
 
1.6%
3 3
 
0.3%
9 1
 
0.1%
4 1
 
0.1%
6 1
 
0.1%
2023-12-09T22:16:00.044066image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 703
79.1%
1 166
 
18.7%
2 14
 
1.6%
3 3
 
0.3%
9 1
 
0.1%
4 1
 
0.1%
6 1
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 889
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 703
79.1%
1 166
 
18.7%
2 14
 
1.6%
3 3
 
0.3%
9 1
 
0.1%
4 1
 
0.1%
6 1
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 889
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 703
79.1%
1 166
 
18.7%
2 14
 
1.6%
3 3
 
0.3%
9 1
 
0.1%
4 1
 
0.1%
6 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 889
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 703
79.1%
1 166
 
18.7%
2 14
 
1.6%
3 3
 
0.3%
9 1
 
0.1%
4 1
 
0.1%
6 1
 
0.1%

q26_2
Text

MISSING 

Distinct4
Distinct (%)0.5%
Missing139
Missing (%)13.9%
Memory size53.2 KiB
2023-12-09T22:16:00.154682image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters861
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 834
96.9%
1 23
 
2.7%
2 3
 
0.3%
3 1
 
0.1%
2023-12-09T22:16:00.376713image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 834
96.9%
1 23
 
2.7%
2 3
 
0.3%
3 1
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 861
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 834
96.9%
1 23
 
2.7%
2 3
 
0.3%
3 1
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 861
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 834
96.9%
1 23
 
2.7%
2 3
 
0.3%
3 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 861
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 834
96.9%
1 23
 
2.7%
2 3
 
0.3%
3 1
 
0.1%

q26_3
Text

MISSING 

Distinct13
Distinct (%)1.4%
Missing75
Missing (%)7.5%
Memory size54.9 KiB
2023-12-09T22:16:00.502736image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.005405405
Min length1

Characters and Unicode

Total characters930
Distinct characters9
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)0.5%

Sample

1st row0
2nd row0
3rd row1
4th row0
5th row1
ValueCountFrequency (%)
0 489
52.9%
1 341
36.9%
2 58
 
6.3%
3 17
 
1.8%
4 6
 
0.6%
5 5
 
0.5%
25 2
 
0.2%
8 2
 
0.2%
12 1
 
0.1%
9 1
 
0.1%
Other values (3) 3
 
0.3%
2023-12-09T22:16:00.749049image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 490
52.7%
1 344
37.0%
2 61
 
6.6%
3 17
 
1.8%
5 7
 
0.8%
4 6
 
0.6%
8 3
 
0.3%
9 1
 
0.1%
6 1
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 930
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 490
52.7%
1 344
37.0%
2 61
 
6.6%
3 17
 
1.8%
5 7
 
0.8%
4 6
 
0.6%
8 3
 
0.3%
9 1
 
0.1%
6 1
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 930
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 490
52.7%
1 344
37.0%
2 61
 
6.6%
3 17
 
1.8%
5 7
 
0.8%
4 6
 
0.6%
8 3
 
0.3%
9 1
 
0.1%
6 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 930
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 490
52.7%
1 344
37.0%
2 61
 
6.6%
3 17
 
1.8%
5 7
 
0.8%
4 6
 
0.6%
8 3
 
0.3%
9 1
 
0.1%
6 1
 
0.1%

q26_4
Text

MISSING 

Distinct9
Distinct (%)1.0%
Missing125
Missing (%)12.5%
Memory size53.6 KiB
2023-12-09T22:16:00.870744image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.002285714
Min length1

Characters and Unicode

Total characters877
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)0.5%

Sample

1st row0
2nd row0
3rd row0
4th row1
5th row0
ValueCountFrequency (%)
0 701
80.1%
1 150
 
17.1%
2 14
 
1.6%
3 4
 
0.5%
4 2
 
0.2%
25 1
 
0.1%
7 1
 
0.1%
6 1
 
0.1%
15 1
 
0.1%
2023-12-09T22:16:01.107017image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 701
79.9%
1 151
 
17.2%
2 15
 
1.7%
3 4
 
0.5%
4 2
 
0.2%
5 2
 
0.2%
7 1
 
0.1%
6 1
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 877
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 701
79.9%
1 151
 
17.2%
2 15
 
1.7%
3 4
 
0.5%
4 2
 
0.2%
5 2
 
0.2%
7 1
 
0.1%
6 1
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 877
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 701
79.9%
1 151
 
17.2%
2 15
 
1.7%
3 4
 
0.5%
4 2
 
0.2%
5 2
 
0.2%
7 1
 
0.1%
6 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 877
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 701
79.9%
1 151
 
17.2%
2 15
 
1.7%
3 4
 
0.5%
4 2
 
0.2%
5 2
 
0.2%
7 1
 
0.1%
6 1
 
0.1%

q26_5
Text

MISSING 

Distinct14
Distinct (%)1.4%
Missing27
Missing (%)2.7%
Memory size56.1 KiB
2023-12-09T22:16:01.235876image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.006166495
Min length1

Characters and Unicode

Total characters979
Distinct characters9
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)0.6%

Sample

1st row0
2nd row0
3rd row1
4th row1
5th row1
ValueCountFrequency (%)
1 508
52.2%
0 339
34.8%
2 90
 
9.2%
3 19
 
2.0%
4 4
 
0.4%
6 3
 
0.3%
25 2
 
0.2%
5 2
 
0.2%
7 1
 
0.1%
12 1
 
0.1%
Other values (4) 4
 
0.4%
2023-12-09T22:16:01.482482image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 511
52.2%
0 340
34.7%
2 95
 
9.7%
3 19
 
1.9%
4 4
 
0.4%
6 4
 
0.4%
5 4
 
0.4%
7 1
 
0.1%
8 1
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 979
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 511
52.2%
0 340
34.7%
2 95
 
9.7%
3 19
 
1.9%
4 4
 
0.4%
6 4
 
0.4%
5 4
 
0.4%
7 1
 
0.1%
8 1
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 979
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 511
52.2%
0 340
34.7%
2 95
 
9.7%
3 19
 
1.9%
4 4
 
0.4%
6 4
 
0.4%
5 4
 
0.4%
7 1
 
0.1%
8 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 979
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 511
52.2%
0 340
34.7%
2 95
 
9.7%
3 19
 
1.9%
4 4
 
0.4%
6 4
 
0.4%
5 4
 
0.4%
7 1
 
0.1%
8 1
 
0.1%

q27_1
Text

MISSING 

Distinct7
Distinct (%)3.8%
Missing815
Missing (%)81.5%
Memory size37.3 KiB
2023-12-09T22:16:01.628622image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length9
Median length8
Mean length7.556756757
Min length5

Characters and Unicode

Total characters1398
Distinct characters15
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1-6 hrs
2nd row7-12 hrs
3rd row0 hrs
4th row1-6 hrs
5th row1-6 hrs
ValueCountFrequency (%)
hrs 185
50.0%
1-6 69
 
18.6%
7-12 53
 
14.3%
31 16
 
4.3%
13-18 15
 
4.1%
0 11
 
3.0%
19-23 11
 
3.0%
24-30 10
 
2.7%
2023-12-09T22:16:01.912432image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
185
13.2%
h 185
13.2%
r 185
13.2%
s 185
13.2%
1 179
12.8%
- 158
11.3%
2 74
 
5.3%
6 69
 
4.9%
7 53
 
3.8%
3 52
 
3.7%
Other values (5) 73
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 555
39.7%
Decimal Number 484
34.6%
Space Separator 185
 
13.2%
Dash Punctuation 158
 
11.3%
Math Symbol 16
 
1.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 179
37.0%
2 74
15.3%
6 69
 
14.3%
7 53
 
11.0%
3 52
 
10.7%
0 21
 
4.3%
8 15
 
3.1%
9 11
 
2.3%
4 10
 
2.1%
Lowercase Letter
ValueCountFrequency (%)
h 185
33.3%
r 185
33.3%
s 185
33.3%
Space Separator
ValueCountFrequency (%)
185
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 158
100.0%
Math Symbol
ValueCountFrequency (%)
+ 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 843
60.3%
Latin 555
39.7%

Most frequent character per script

Common
ValueCountFrequency (%)
185
21.9%
1 179
21.2%
- 158
18.7%
2 74
 
8.8%
6 69
 
8.2%
7 53
 
6.3%
3 52
 
6.2%
0 21
 
2.5%
+ 16
 
1.9%
8 15
 
1.8%
Other values (2) 21
 
2.5%
Latin
ValueCountFrequency (%)
h 185
33.3%
r 185
33.3%
s 185
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1398
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
185
13.2%
h 185
13.2%
r 185
13.2%
s 185
13.2%
1 179
12.8%
- 158
11.3%
2 74
 
5.3%
6 69
 
4.9%
7 53
 
3.8%
3 52
 
3.7%
Other values (5) 73
 
5.2%

q27_2
Text

MISSING 

Distinct6
Distinct (%)23.1%
Missing974
Missing (%)97.4%
Memory size32.2 KiB
2023-12-09T22:16:02.062143image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length9
Median length7
Mean length7.153846154
Min length5

Characters and Unicode

Total characters186
Distinct characters14
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)3.8%

Sample

1st row1-6 hrs
2nd row1-6 hrs
3rd row13-18 hrs
4th row19-23 hrs
5th row0 hrs
ValueCountFrequency (%)
hrs 26
50.0%
1-6 13
25.0%
7-12 4
 
7.7%
0 4
 
7.7%
13-18 2
 
3.8%
19-23 2
 
3.8%
31 1
 
1.9%
2023-12-09T22:16:02.360392image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
26
14.0%
h 26
14.0%
r 26
14.0%
s 26
14.0%
1 24
12.9%
- 21
11.3%
6 13
7.0%
2 6
 
3.2%
3 5
 
2.7%
7 4
 
2.2%
Other values (4) 9
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 78
41.9%
Decimal Number 60
32.3%
Space Separator 26
 
14.0%
Dash Punctuation 21
 
11.3%
Math Symbol 1
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 24
40.0%
6 13
21.7%
2 6
 
10.0%
3 5
 
8.3%
7 4
 
6.7%
0 4
 
6.7%
8 2
 
3.3%
9 2
 
3.3%
Lowercase Letter
ValueCountFrequency (%)
h 26
33.3%
r 26
33.3%
s 26
33.3%
Space Separator
ValueCountFrequency (%)
26
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 108
58.1%
Latin 78
41.9%

Most frequent character per script

Common
ValueCountFrequency (%)
26
24.1%
1 24
22.2%
- 21
19.4%
6 13
12.0%
2 6
 
5.6%
3 5
 
4.6%
7 4
 
3.7%
0 4
 
3.7%
8 2
 
1.9%
9 2
 
1.9%
Latin
ValueCountFrequency (%)
h 26
33.3%
r 26
33.3%
s 26
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 186
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
26
14.0%
h 26
14.0%
r 26
14.0%
s 26
14.0%
1 24
12.9%
- 21
11.3%
6 13
7.0%
2 6
 
3.2%
3 5
 
2.7%
7 4
 
2.2%
Other values (4) 9
 
4.8%

q27_3
Text

MISSING 

Distinct7
Distinct (%)1.6%
Missing566
Missing (%)56.6%
Memory size45.2 KiB
2023-12-09T22:16:02.506291image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length9
Median length8
Mean length7.68202765
Min length5

Characters and Unicode

Total characters3334
Distinct characters15
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1-6 hrs
2nd row24-30 hrs
3rd row1-6 hrs
4th row1-6 hrs
5th row1-6 hrs
ValueCountFrequency (%)
hrs 434
50.0%
1-6 153
 
17.6%
7-12 106
 
12.2%
19-23 45
 
5.2%
13-18 42
 
4.8%
31 42
 
4.8%
24-30 27
 
3.1%
0 19
 
2.2%
2023-12-09T22:16:02.783257image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
434
13.0%
h 434
13.0%
r 434
13.0%
s 434
13.0%
1 430
12.9%
- 373
11.2%
2 178
5.3%
3 156
 
4.7%
6 153
 
4.6%
7 106
 
3.2%
Other values (5) 202
6.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1302
39.1%
Decimal Number 1183
35.5%
Space Separator 434
 
13.0%
Dash Punctuation 373
 
11.2%
Math Symbol 42
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 430
36.3%
2 178
15.0%
3 156
 
13.2%
6 153
 
12.9%
7 106
 
9.0%
0 46
 
3.9%
9 45
 
3.8%
8 42
 
3.6%
4 27
 
2.3%
Lowercase Letter
ValueCountFrequency (%)
h 434
33.3%
r 434
33.3%
s 434
33.3%
Space Separator
ValueCountFrequency (%)
434
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 373
100.0%
Math Symbol
ValueCountFrequency (%)
+ 42
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2032
60.9%
Latin 1302
39.1%

Most frequent character per script

Common
ValueCountFrequency (%)
434
21.4%
1 430
21.2%
- 373
18.4%
2 178
8.8%
3 156
 
7.7%
6 153
 
7.5%
7 106
 
5.2%
0 46
 
2.3%
9 45
 
2.2%
8 42
 
2.1%
Other values (2) 69
 
3.4%
Latin
ValueCountFrequency (%)
h 434
33.3%
r 434
33.3%
s 434
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3334
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
434
13.0%
h 434
13.0%
r 434
13.0%
s 434
13.0%
1 430
12.9%
- 373
11.2%
2 178
5.3%
3 156
 
4.7%
6 153
 
4.6%
7 106
 
3.2%
Other values (5) 202
6.1%

q27_4
Text

MISSING 

Distinct7
Distinct (%)4.0%
Missing827
Missing (%)82.7%
Memory size36.9 KiB
2023-12-09T22:16:02.930550image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length9
Median length8
Mean length7.710982659
Min length5

Characters and Unicode

Total characters1334
Distinct characters15
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row7-12 hrs
2nd row1-6 hrs
3rd row7-12 hrs
4th row7-12 hrs
5th row1-6 hrs
ValueCountFrequency (%)
hrs 173
50.0%
1-6 64
 
18.5%
7-12 47
 
13.6%
13-18 17
 
4.9%
19-23 14
 
4.0%
24-30 13
 
3.8%
31 12
 
3.5%
0 6
 
1.7%
2023-12-09T22:16:03.215834image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
173
13.0%
h 173
13.0%
r 173
13.0%
s 173
13.0%
1 171
12.8%
- 155
11.6%
2 74
5.5%
6 64
 
4.8%
3 56
 
4.2%
7 47
 
3.5%
Other values (5) 75
5.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 519
38.9%
Decimal Number 475
35.6%
Space Separator 173
 
13.0%
Dash Punctuation 155
 
11.6%
Math Symbol 12
 
0.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 171
36.0%
2 74
15.6%
6 64
 
13.5%
3 56
 
11.8%
7 47
 
9.9%
0 19
 
4.0%
8 17
 
3.6%
9 14
 
2.9%
4 13
 
2.7%
Lowercase Letter
ValueCountFrequency (%)
h 173
33.3%
r 173
33.3%
s 173
33.3%
Space Separator
ValueCountFrequency (%)
173
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 155
100.0%
Math Symbol
ValueCountFrequency (%)
+ 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 815
61.1%
Latin 519
38.9%

Most frequent character per script

Common
ValueCountFrequency (%)
173
21.2%
1 171
21.0%
- 155
19.0%
2 74
9.1%
6 64
 
7.9%
3 56
 
6.9%
7 47
 
5.8%
0 19
 
2.3%
8 17
 
2.1%
9 14
 
1.7%
Other values (2) 25
 
3.1%
Latin
ValueCountFrequency (%)
h 173
33.3%
r 173
33.3%
s 173
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1334
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
173
13.0%
h 173
13.0%
r 173
13.0%
s 173
13.0%
1 171
12.8%
- 155
11.6%
2 74
5.5%
6 64
 
4.8%
3 56
 
4.2%
7 47
 
3.5%
Other values (5) 75
5.6%

q27_5
Text

MISSING 

Distinct7
Distinct (%)1.1%
Missing369
Missing (%)36.9%
Memory size51.6 KiB
2023-12-09T22:16:03.364175image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length9
Median length8
Mean length7.754358162
Min length5

Characters and Unicode

Total characters4893
Distinct characters15
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1-6 hrs
2nd row7-12 hrs
3rd row24-30 hrs
4th row1-6 hrs
5th row31+ hrs
ValueCountFrequency (%)
hrs 631
50.0%
1-6 232
 
18.4%
7-12 154
 
12.2%
13-18 80
 
6.3%
19-23 57
 
4.5%
31 52
 
4.1%
24-30 40
 
3.2%
0 16
 
1.3%
2023-12-09T22:16:03.647979image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 655
13.4%
631
12.9%
h 631
12.9%
r 631
12.9%
s 631
12.9%
- 563
11.5%
2 251
 
5.1%
6 232
 
4.7%
3 229
 
4.7%
7 154
 
3.1%
Other values (5) 285
5.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1893
38.7%
Decimal Number 1754
35.8%
Space Separator 631
 
12.9%
Dash Punctuation 563
 
11.5%
Math Symbol 52
 
1.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 655
37.3%
2 251
 
14.3%
6 232
 
13.2%
3 229
 
13.1%
7 154
 
8.8%
8 80
 
4.6%
9 57
 
3.2%
0 56
 
3.2%
4 40
 
2.3%
Lowercase Letter
ValueCountFrequency (%)
h 631
33.3%
r 631
33.3%
s 631
33.3%
Space Separator
ValueCountFrequency (%)
631
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 563
100.0%
Math Symbol
ValueCountFrequency (%)
+ 52
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3000
61.3%
Latin 1893
38.7%

Most frequent character per script

Common
ValueCountFrequency (%)
1 655
21.8%
631
21.0%
- 563
18.8%
2 251
 
8.4%
6 232
 
7.7%
3 229
 
7.6%
7 154
 
5.1%
8 80
 
2.7%
9 57
 
1.9%
0 56
 
1.9%
Other values (2) 92
 
3.1%
Latin
ValueCountFrequency (%)
h 631
33.3%
r 631
33.3%
s 631
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4893
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 655
13.4%
631
12.9%
h 631
12.9%
r 631
12.9%
s 631
12.9%
- 563
11.5%
2 251
 
5.1%
6 232
 
4.7%
3 229
 
4.7%
7 154
 
3.1%
Other values (5) 285
5.8%

q28_1
Text

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size56.8 KiB
2023-12-09T22:16:03.764093image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row1
4th row1
5th row1
ValueCountFrequency (%)
1 643
64.3%
0 357
35.7%
2023-12-09T22:16:03.998908image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 643
64.3%
0 357
35.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 643
64.3%
0 357
35.7%

Most occurring scripts

ValueCountFrequency (%)
Common 1000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 643
64.3%
0 357
35.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 643
64.3%
0 357
35.7%

q28_2
Text

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size56.8 KiB
2023-12-09T22:16:04.111971image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row1
5th row1
ValueCountFrequency (%)
0 820
82.0%
1 180
 
18.0%
2023-12-09T22:16:04.350380image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 820
82.0%
1 180
 
18.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 820
82.0%
1 180
 
18.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 820
82.0%
1 180
 
18.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 820
82.0%
1 180
 
18.0%

q28_3
Text

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size56.8 KiB
2023-12-09T22:16:04.459455image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row1
5th row0
ValueCountFrequency (%)
0 927
92.7%
1 73
 
7.3%
2023-12-09T22:16:04.676561image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 927
92.7%
1 73
 
7.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 927
92.7%
1 73
 
7.3%

Most occurring scripts

ValueCountFrequency (%)
Common 1000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 927
92.7%
1 73
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 927
92.7%
1 73
 
7.3%

q28_4
Text

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size56.8 KiB
2023-12-09T22:16:04.784300image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row1
ValueCountFrequency (%)
0 597
59.7%
1 403
40.3%
2023-12-09T22:16:05.003312image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 597
59.7%
1 403
40.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 597
59.7%
1 403
40.3%

Most occurring scripts

ValueCountFrequency (%)
Common 1000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 597
59.7%
1 403
40.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 597
59.7%
1 403
40.3%

q28_5
Text

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size56.8 KiB
2023-12-09T22:16:05.110810image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 807
80.7%
1 193
 
19.3%
2023-12-09T22:16:05.336381image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 807
80.7%
1 193
 
19.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 807
80.7%
1 193
 
19.3%

Most occurring scripts

ValueCountFrequency (%)
Common 1000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 807
80.7%
1 193
 
19.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 807
80.7%
1 193
 
19.3%

q28_6
Text

Distinct84
Distinct (%)8.4%
Missing1
Missing (%)0.1%
Memory size58.8 KiB
2023-12-09T22:16:05.640829image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length87
Median length1
Mean length3.07007007
Min length1

Characters and Unicode

Total characters3067
Distinct characters67
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique80 ?
Unique (%)8.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th rowUnion Workshop
ValueCountFrequency (%)
0 910
74.5%
and 13
 
1.1%
music 13
 
1.1%
arts 11
 
0.9%
the 9
 
0.7%
of 8
 
0.7%
online 7
 
0.6%
professional 6
 
0.5%
education 5
 
0.4%
state 5
 
0.4%
Other values (170) 235
 
19.2%
2023-12-09T22:16:06.122235image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 910
29.7%
224
 
7.3%
e 147
 
4.8%
a 137
 
4.5%
n 132
 
4.3%
o 130
 
4.2%
i 128
 
4.2%
t 124
 
4.0%
r 123
 
4.0%
s 96
 
3.1%
Other values (57) 916
29.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1493
48.7%
Decimal Number 914
29.8%
Uppercase Letter 379
 
12.4%
Space Separator 224
 
7.3%
Other Punctuation 50
 
1.6%
Close Punctuation 3
 
0.1%
Open Punctuation 3
 
0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 147
9.8%
a 137
9.2%
n 132
 
8.8%
o 130
 
8.7%
i 128
 
8.6%
t 124
 
8.3%
r 123
 
8.2%
s 96
 
6.4%
l 69
 
4.6%
u 66
 
4.4%
Other values (16) 341
22.8%
Uppercase Letter
ValueCountFrequency (%)
A 51
13.5%
S 38
 
10.0%
C 30
 
7.9%
T 29
 
7.7%
N 27
 
7.1%
E 26
 
6.9%
M 25
 
6.6%
O 18
 
4.7%
D 17
 
4.5%
P 17
 
4.5%
Other values (15) 101
26.6%
Other Punctuation
ValueCountFrequency (%)
, 27
54.0%
/ 9
 
18.0%
. 8
 
16.0%
: 2
 
4.0%
; 2
 
4.0%
' 1
 
2.0%
& 1
 
2.0%
Decimal Number
ValueCountFrequency (%)
0 910
99.6%
2 1
 
0.1%
1 1
 
0.1%
3 1
 
0.1%
4 1
 
0.1%
Space Separator
ValueCountFrequency (%)
224
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1872
61.0%
Common 1195
39.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 147
 
7.9%
a 137
 
7.3%
n 132
 
7.1%
o 130
 
6.9%
i 128
 
6.8%
t 124
 
6.6%
r 123
 
6.6%
s 96
 
5.1%
l 69
 
3.7%
u 66
 
3.5%
Other values (41) 720
38.5%
Common
ValueCountFrequency (%)
0 910
76.2%
224
 
18.7%
, 27
 
2.3%
/ 9
 
0.8%
. 8
 
0.7%
) 3
 
0.3%
( 3
 
0.3%
: 2
 
0.2%
; 2
 
0.2%
' 1
 
0.1%
Other values (6) 6
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3067
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 910
29.7%
224
 
7.3%
e 147
 
4.8%
a 137
 
4.5%
n 132
 
4.3%
o 130
 
4.2%
i 128
 
4.2%
t 124
 
4.0%
r 123
 
4.0%
s 96
 
3.1%
Other values (57) 916
29.9%

q40_r1_c1_1
Text

MISSING 

Distinct216
Distinct (%)30.6%
Missing293
Missing (%)29.3%
Memory size61.6 KiB
2023-12-09T22:16:06.532353image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length63
Median length38
Mean length18.79632249
Min length3

Characters and Unicode

Total characters13289
Distinct characters66
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique103 ?
Unique (%)14.6%

Sample

1st rowArts for All
2nd rowThird Street Music School Settlement
3rd rowThird Street Music School Settlement
4th rowOTHER
5th rowScript to Stage
ValueCountFrequency (%)
arts 91
 
4.4%
other 64
 
3.1%
museum 55
 
2.7%
dance 48
 
2.3%
of 47
 
2.3%
center 41
 
2.0%
theatre 36
 
1.8%
in 36
 
1.8%
broadway 35
 
1.7%
the 33
 
1.6%
Other values (345) 1561
76.3%
2023-12-09T22:16:07.118181image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1340
 
10.1%
e 1029
 
7.7%
n 906
 
6.8%
r 875
 
6.6%
o 867
 
6.5%
t 827
 
6.2%
a 795
 
6.0%
i 705
 
5.3%
s 485
 
3.6%
u 481
 
3.6%
Other values (56) 4979
37.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 9502
71.5%
Uppercase Letter 2274
 
17.1%
Space Separator 1340
 
10.1%
Other Punctuation 76
 
0.6%
Decimal Number 49
 
0.4%
Open Punctuation 20
 
0.2%
Close Punctuation 20
 
0.2%
Dash Punctuation 7
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1029
10.8%
n 906
9.5%
r 875
9.2%
o 867
9.1%
t 827
 
8.7%
a 795
 
8.4%
i 705
 
7.4%
s 485
 
5.1%
u 481
 
5.1%
l 438
 
4.6%
Other values (16) 2094
22.0%
Uppercase Letter
ValueCountFrequency (%)
A 320
14.1%
C 253
11.1%
M 188
 
8.3%
T 178
 
7.8%
S 163
 
7.2%
E 137
 
6.0%
B 121
 
5.3%
R 109
 
4.8%
P 99
 
4.4%
H 98
 
4.3%
Other values (15) 608
26.7%
Other Punctuation
ValueCountFrequency (%)
& 22
28.9%
. 21
27.6%
' 16
21.1%
, 8
 
10.5%
/ 5
 
6.6%
: 4
 
5.3%
Decimal Number
ValueCountFrequency (%)
2 22
44.9%
1 13
26.5%
9 13
26.5%
4 1
 
2.0%
Space Separator
ValueCountFrequency (%)
1340
100.0%
Open Punctuation
ValueCountFrequency (%)
( 20
100.0%
Close Punctuation
ValueCountFrequency (%)
) 20
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 11776
88.6%
Common 1513
 
11.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1029
 
8.7%
n 906
 
7.7%
r 875
 
7.4%
o 867
 
7.4%
t 827
 
7.0%
a 795
 
6.8%
i 705
 
6.0%
s 485
 
4.1%
u 481
 
4.1%
l 438
 
3.7%
Other values (41) 4368
37.1%
Common
ValueCountFrequency (%)
1340
88.6%
& 22
 
1.5%
2 22
 
1.5%
. 21
 
1.4%
( 20
 
1.3%
) 20
 
1.3%
' 16
 
1.1%
1 13
 
0.9%
9 13
 
0.9%
, 8
 
0.5%
Other values (5) 18
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13289
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1340
 
10.1%
e 1029
 
7.7%
n 906
 
6.8%
r 875
 
6.6%
o 867
 
6.5%
t 827
 
6.2%
a 795
 
6.0%
i 705
 
5.3%
s 485
 
3.6%
u 481
 
3.6%
Other values (56) 4979
37.5%

q40_r1_c2_1
Text

MISSING 

Distinct63
Distinct (%)98.4%
Missing936
Missing (%)93.6%
Memory size34.1 KiB
2023-12-09T22:16:07.487835image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length39
Median length25
Mean length19.390625
Min length6

Characters and Unicode

Total characters1241
Distinct characters58
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique62 ?
Unique (%)96.9%

Sample

1st rowDorill Initiative
2nd rowPhoenix Theatre
3rd rowELAS Grant
4th rowPowerHouse
5th rowReplications Inc.
ValueCountFrequency (%)
of 6
 
3.1%
art 5
 
2.6%
dance 5
 
2.6%
arts 4
 
2.0%
a 3
 
1.5%
theatre 3
 
1.5%
keys 3
 
1.5%
studio 3
 
1.5%
broadway 3
 
1.5%
american 3
 
1.5%
Other values (138) 158
80.6%
2023-12-09T22:16:08.020806image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
133
 
10.7%
e 98
 
7.9%
a 90
 
7.3%
r 89
 
7.2%
o 74
 
6.0%
t 66
 
5.3%
i 62
 
5.0%
n 58
 
4.7%
s 51
 
4.1%
l 44
 
3.5%
Other values (48) 476
38.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 883
71.2%
Uppercase Letter 202
 
16.3%
Space Separator 133
 
10.7%
Other Punctuation 15
 
1.2%
Dash Punctuation 4
 
0.3%
Decimal Number 4
 
0.3%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 37
18.3%
D 17
 
8.4%
S 17
 
8.4%
C 13
 
6.4%
B 13
 
6.4%
M 13
 
6.4%
P 13
 
6.4%
T 11
 
5.4%
E 10
 
5.0%
L 8
 
4.0%
Other values (15) 50
24.8%
Lowercase Letter
ValueCountFrequency (%)
e 98
11.1%
a 90
10.2%
r 89
10.1%
o 74
 
8.4%
t 66
 
7.5%
i 62
 
7.0%
n 58
 
6.6%
s 51
 
5.8%
l 44
 
5.0%
c 43
 
4.9%
Other values (14) 208
23.6%
Other Punctuation
ValueCountFrequency (%)
. 9
60.0%
' 2
 
13.3%
& 2
 
13.3%
! 1
 
6.7%
, 1
 
6.7%
Decimal Number
ValueCountFrequency (%)
4 3
75.0%
2 1
 
25.0%
Space Separator
ValueCountFrequency (%)
133
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1085
87.4%
Common 156
 
12.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 98
 
9.0%
a 90
 
8.3%
r 89
 
8.2%
o 74
 
6.8%
t 66
 
6.1%
i 62
 
5.7%
n 58
 
5.3%
s 51
 
4.7%
l 44
 
4.1%
c 43
 
4.0%
Other values (39) 410
37.8%
Common
ValueCountFrequency (%)
133
85.3%
. 9
 
5.8%
- 4
 
2.6%
4 3
 
1.9%
' 2
 
1.3%
& 2
 
1.3%
! 1
 
0.6%
2 1
 
0.6%
, 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1241
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
133
 
10.7%
e 98
 
7.9%
a 90
 
7.3%
r 89
 
7.2%
o 74
 
6.0%
t 66
 
5.3%
i 62
 
5.0%
n 58
 
4.7%
s 51
 
4.1%
l 44
 
3.5%
Other values (48) 476
38.4%

q40_r1_c3_1
Text

MISSING 

Distinct6
Distinct (%)0.9%
Missing303
Missing (%)30.3%
Memory size53.3 KiB
2023-12-09T22:16:08.212080image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length11
Median length10
Mean length7.183644189
Min length5

Characters and Unicode

Total characters5007
Distinct characters22
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowVisual Arts
2nd rowVisual Arts
3rd rowMusic
4th rowDance
5th rowTheater
ValueCountFrequency (%)
visual 189
21.3%
arts 189
21.3%
dance 175
19.8%
theater 144
16.3%
music 141
15.9%
other 28
 
3.2%
film/media 20
 
2.3%
2023-12-09T22:16:08.539347image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 528
10.5%
s 519
 
10.4%
e 511
 
10.2%
i 370
 
7.4%
r 361
 
7.2%
t 361
 
7.2%
u 330
 
6.6%
c 316
 
6.3%
l 209
 
4.2%
V 189
 
3.8%
Other values (12) 1313
26.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3892
77.7%
Uppercase Letter 906
 
18.1%
Space Separator 189
 
3.8%
Other Punctuation 20
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 528
13.6%
s 519
13.3%
e 511
13.1%
i 370
9.5%
r 361
9.3%
t 361
9.3%
u 330
8.5%
c 316
8.1%
l 209
 
5.4%
n 175
 
4.5%
Other values (3) 212
5.4%
Uppercase Letter
ValueCountFrequency (%)
V 189
20.9%
A 189
20.9%
D 175
19.3%
M 161
17.8%
T 144
15.9%
O 28
 
3.1%
F 20
 
2.2%
Space Separator
ValueCountFrequency (%)
189
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4798
95.8%
Common 209
 
4.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 528
11.0%
s 519
10.8%
e 511
10.7%
i 370
 
7.7%
r 361
 
7.5%
t 361
 
7.5%
u 330
 
6.9%
c 316
 
6.6%
l 209
 
4.4%
V 189
 
3.9%
Other values (10) 1104
23.0%
Common
ValueCountFrequency (%)
189
90.4%
/ 20
 
9.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5007
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 528
10.5%
s 519
 
10.4%
e 511
 
10.2%
i 370
 
7.4%
r 361
 
7.2%
t 361
 
7.2%
u 330
 
6.6%
c 316
 
6.3%
l 209
 
4.2%
V 189
 
3.8%
Other values (12) 1313
26.2%

q40_r1_c4_1
Text

MISSING 

Distinct4
Distinct (%)0.6%
Missing312
Missing (%)31.2%
Memory size73.0 KiB
2023-12-09T22:16:08.740304image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length42
Median length42
Mean length36.99273256
Min length24

Characters and Unicode

Total characters25451
Distinct characters32
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowResidency (direct instruction to students)
2nd rowResidency (direct instruction to students)
3rd rowResidency (direct instruction to students)
4th rowResidency (direct instruction to students)
5th rowResidency (direct instruction to students)
ValueCountFrequency (%)
residency 454
14.9%
direct 454
14.9%
instruction 454
14.9%
to 454
14.9%
students 454
14.9%
in-school 117
 
3.9%
student 117
 
3.9%
workshops 117
 
3.9%
arts 65
 
2.1%
related 65
 
2.1%
Other values (5) 286
9.4%
2023-12-09T22:16:09.075482image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 3140
12.3%
e 2440
9.6%
s 2401
9.4%
2349
9.2%
n 2154
8.5%
i 1998
 
7.9%
d 1609
 
6.3%
o 1532
 
6.0%
c 1531
 
6.0%
r 1259
 
4.9%
Other values (22) 5038
19.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 20856
81.9%
Space Separator 2349
 
9.2%
Uppercase Letter 1221
 
4.8%
Open Punctuation 454
 
1.8%
Close Punctuation 454
 
1.8%
Dash Punctuation 117
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 3140
15.1%
e 2440
11.7%
s 2401
11.5%
n 2154
10.3%
i 1998
9.6%
d 1609
7.7%
o 1532
7.3%
c 1531
7.3%
r 1259
6.0%
u 1025
 
4.9%
Other values (9) 1767
8.5%
Uppercase Letter
ValueCountFrequency (%)
R 519
42.5%
T 117
 
9.6%
W 117
 
9.6%
S 117
 
9.6%
I 117
 
9.6%
A 65
 
5.3%
F 65
 
5.3%
P 52
 
4.3%
D 52
 
4.3%
Space Separator
ValueCountFrequency (%)
2349
100.0%
Open Punctuation
ValueCountFrequency (%)
( 454
100.0%
Close Punctuation
ValueCountFrequency (%)
) 454
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 117
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 22077
86.7%
Common 3374
 
13.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 3140
14.2%
e 2440
11.1%
s 2401
10.9%
n 2154
9.8%
i 1998
9.1%
d 1609
7.3%
o 1532
6.9%
c 1531
6.9%
r 1259
5.7%
u 1025
 
4.6%
Other values (18) 2988
13.5%
Common
ValueCountFrequency (%)
2349
69.6%
( 454
 
13.5%
) 454
 
13.5%
- 117
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 25451
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 3140
12.3%
e 2440
9.6%
s 2401
9.4%
2349
9.2%
n 2154
8.5%
i 1998
 
7.9%
d 1609
 
6.3%
o 1532
 
6.0%
c 1531
 
6.0%
r 1259
 
4.9%
Other values (22) 5038
19.8%

q40_r1_c5_1
Text

MISSING 

Distinct4
Distinct (%)0.6%
Missing308
Missing (%)30.8%
Memory size48.9 KiB
2023-12-09T22:16:09.198258image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters692
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row4
2nd row5
3rd row4
4th row4
5th row5
ValueCountFrequency (%)
5 589
85.1%
4 84
 
12.1%
3 18
 
2.6%
2 1
 
0.1%
2023-12-09T22:16:09.426626image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 589
85.1%
4 84
 
12.1%
3 18
 
2.6%
2 1
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 692
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 589
85.1%
4 84
 
12.1%
3 18
 
2.6%
2 1
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 692
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 589
85.1%
4 84
 
12.1%
3 18
 
2.6%
2 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 692
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 589
85.1%
4 84
 
12.1%
3 18
 
2.6%
2 1
 
0.1%

q40_r1_c6_1
Text

MISSING 

Distinct186
Distinct (%)27.8%
Missing330
Missing (%)33.0%
Memory size49.3 KiB
2023-12-09T22:16:09.894919image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length4
Median length2
Mean length2.388059701
Min length1

Characters and Unicode

Total characters1600
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique108 ?
Unique (%)16.1%

Sample

1st row90
2nd row200
3rd row12
4th row75
5th row31
ValueCountFrequency (%)
100 34
 
5.1%
30 33
 
4.9%
25 33
 
4.9%
50 32
 
4.8%
200 27
 
4.0%
60 24
 
3.6%
20 24
 
3.6%
10 21
 
3.1%
120 19
 
2.8%
150 19
 
2.8%
Other values (176) 404
60.3%
2023-12-09T22:16:10.508958image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 472
29.5%
5 241
15.1%
1 219
13.7%
2 209
13.1%
3 119
 
7.4%
4 86
 
5.4%
6 75
 
4.7%
7 66
 
4.1%
8 64
 
4.0%
9 49
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1600
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 472
29.5%
5 241
15.1%
1 219
13.7%
2 209
13.1%
3 119
 
7.4%
4 86
 
5.4%
6 75
 
4.7%
7 66
 
4.1%
8 64
 
4.0%
9 49
 
3.1%

Most occurring scripts

ValueCountFrequency (%)
Common 1600
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 472
29.5%
5 241
15.1%
1 219
13.7%
2 209
13.1%
3 119
 
7.4%
4 86
 
5.4%
6 75
 
4.7%
7 66
 
4.1%
8 64
 
4.0%
9 49
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1600
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 472
29.5%
5 241
15.1%
1 219
13.7%
2 209
13.1%
3 119
 
7.4%
4 86
 
5.4%
6 75
 
4.7%
7 66
 
4.1%
8 64
 
4.0%
9 49
 
3.1%

q40_r1_c7_1
Text

MISSING 

Distinct71
Distinct (%)10.8%
Missing344
Missing (%)34.4%
Memory size48.5 KiB
2023-12-09T22:16:10.789313image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length4
Median length2
Mean length1.704268293
Min length1

Characters and Unicode

Total characters1118
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)3.8%

Sample

1st row6
2nd row30
3rd row15
4th row17
5th row9
ValueCountFrequency (%)
10 87
 
13.3%
20 56
 
8.5%
1 49
 
7.5%
6 35
 
5.3%
30 33
 
5.0%
12 28
 
4.3%
2 27
 
4.1%
5 27
 
4.1%
40 26
 
4.0%
3 24
 
3.7%
Other values (61) 264
40.2%
2023-12-09T22:16:11.210386image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 291
26.0%
1 243
21.7%
2 161
14.4%
5 114
 
10.2%
4 83
 
7.4%
3 80
 
7.2%
6 65
 
5.8%
8 40
 
3.6%
7 30
 
2.7%
9 11
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1118
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 291
26.0%
1 243
21.7%
2 161
14.4%
5 114
 
10.2%
4 83
 
7.4%
3 80
 
7.2%
6 65
 
5.8%
8 40
 
3.6%
7 30
 
2.7%
9 11
 
1.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1118
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 291
26.0%
1 243
21.7%
2 161
14.4%
5 114
 
10.2%
4 83
 
7.4%
3 80
 
7.2%
6 65
 
5.8%
8 40
 
3.6%
7 30
 
2.7%
9 11
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1118
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 291
26.0%
1 243
21.7%
2 161
14.4%
5 114
 
10.2%
4 83
 
7.4%
3 80
 
7.2%
6 65
 
5.8%
8 40
 
3.6%
7 30
 
2.7%
9 11
 
1.0%

q40_r1_c8_1
Text

MISSING 

Distinct3
Distinct (%)0.4%
Missing312
Missing (%)31.2%
Memory size50.8 KiB
2023-12-09T22:16:11.363662image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length9
Median length3
Mean length3.882267442
Min length2

Characters and Unicode

Total characters2671
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowUncertain
2nd rowYes
3rd rowYes
4th rowYes
5th rowYes
ValueCountFrequency (%)
yes 574
83.4%
uncertain 103
 
15.0%
no 11
 
1.6%
2023-12-09T22:16:11.638738image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 677
25.3%
Y 574
21.5%
s 574
21.5%
n 206
 
7.7%
U 103
 
3.9%
c 103
 
3.9%
r 103
 
3.9%
t 103
 
3.9%
a 103
 
3.9%
i 103
 
3.9%
Other values (2) 22
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1983
74.2%
Uppercase Letter 688
 
25.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 677
34.1%
s 574
28.9%
n 206
 
10.4%
c 103
 
5.2%
r 103
 
5.2%
t 103
 
5.2%
a 103
 
5.2%
i 103
 
5.2%
o 11
 
0.6%
Uppercase Letter
ValueCountFrequency (%)
Y 574
83.4%
U 103
 
15.0%
N 11
 
1.6%

Most occurring scripts

ValueCountFrequency (%)
Latin 2671
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 677
25.3%
Y 574
21.5%
s 574
21.5%
n 206
 
7.7%
U 103
 
3.9%
c 103
 
3.9%
r 103
 
3.9%
t 103
 
3.9%
a 103
 
3.9%
i 103
 
3.9%
Other values (2) 22
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2671
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 677
25.3%
Y 574
21.5%
s 574
21.5%
n 206
 
7.7%
U 103
 
3.9%
c 103
 
3.9%
r 103
 
3.9%
t 103
 
3.9%
a 103
 
3.9%
i 103
 
3.9%
Other values (2) 22
 
0.8%

q40_r1_c9
Text

MISSING 

Distinct3
Distinct (%)6.8%
Missing956
Missing (%)95.6%
Memory size32.9 KiB
2023-12-09T22:16:11.802635image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length21
Median length5
Mean length9.727272727
Min length5

Characters and Unicode

Total characters428
Distinct characters19
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowOther
2nd rowOther
3rd rowOther
4th rowOther
5th rowHigh cost of services
ValueCountFrequency (%)
other 31
39.7%
high 8
 
10.3%
cost 8
 
10.3%
of 8
 
10.3%
services 8
 
10.3%
reduced 5
 
6.4%
school 5
 
6.4%
budget 5
 
6.4%
2023-12-09T22:16:12.111639image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 62
14.5%
h 44
10.3%
t 44
10.3%
r 39
9.1%
34
7.9%
O 31
7.2%
s 29
 
6.8%
o 26
 
6.1%
c 26
 
6.1%
i 16
 
3.7%
Other values (9) 77
18.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 350
81.8%
Uppercase Letter 44
 
10.3%
Space Separator 34
 
7.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 62
17.7%
h 44
12.6%
t 44
12.6%
r 39
11.1%
s 29
8.3%
o 26
7.4%
c 26
7.4%
i 16
 
4.6%
d 15
 
4.3%
g 13
 
3.7%
Other values (5) 36
10.3%
Uppercase Letter
ValueCountFrequency (%)
O 31
70.5%
H 8
 
18.2%
R 5
 
11.4%
Space Separator
ValueCountFrequency (%)
34
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 394
92.1%
Common 34
 
7.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 62
15.7%
h 44
11.2%
t 44
11.2%
r 39
9.9%
O 31
7.9%
s 29
7.4%
o 26
6.6%
c 26
6.6%
i 16
 
4.1%
d 15
 
3.8%
Other values (8) 62
15.7%
Common
ValueCountFrequency (%)
34
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 428
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 62
14.5%
h 44
10.3%
t 44
10.3%
r 39
9.1%
34
7.9%
O 31
7.2%
s 29
 
6.8%
o 26
 
6.1%
c 26
 
6.1%
i 16
 
3.7%
Other values (9) 77
18.0%

q40_r1_c10_1
Text

MISSING 

Distinct31
Distinct (%)96.9%
Missing968
Missing (%)96.8%
Memory size33.7 KiB
2023-12-09T22:16:13.684125image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length363
Median length37
Mean length48.375
Min length6

Characters and Unicode

Total characters1548
Distinct characters49
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)93.8%

Sample

1st rowgrant comes to an end.
2nd rowGrant expired, expecting renewal
3rd rowfunding/grant
4th rowIf was funded by a grant - not sure we can afford it on our own
5th rowCarry over funds from Covid. They were very eager to help with the grant process but did not live up to expectations in the arts classrooms, even prior to the pandemic. Artists in residence very from experience working with students, to lack of patience working with students in a title 1 school, and wavering on a clear artistic vision that gave the kids buy in.
ValueCountFrequency (%)
to 16
 
5.7%
grant 14
 
5.0%
a 10
 
3.5%
the 9
 
3.2%
year 6
 
2.1%
we 6
 
2.1%
and 6
 
2.1%
not 5
 
1.8%
was 5
 
1.8%
this 5
 
1.8%
Other values (138) 200
70.9%
2023-12-09T22:16:14.291382image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
251
16.2%
e 155
 
10.0%
t 111
 
7.2%
r 101
 
6.5%
a 95
 
6.1%
n 94
 
6.1%
o 90
 
5.8%
i 83
 
5.4%
s 64
 
4.1%
d 59
 
3.8%
Other values (39) 445
28.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1213
78.4%
Space Separator 251
 
16.2%
Uppercase Letter 61
 
3.9%
Other Punctuation 20
 
1.3%
Dash Punctuation 2
 
0.1%
Decimal Number 1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 155
12.8%
t 111
 
9.2%
r 101
 
8.3%
a 95
 
7.8%
n 94
 
7.7%
o 90
 
7.4%
i 83
 
6.8%
s 64
 
5.3%
d 59
 
4.9%
h 40
 
3.3%
Other values (14) 321
26.5%
Uppercase Letter
ValueCountFrequency (%)
G 6
9.8%
F 6
9.8%
A 6
9.8%
C 6
9.8%
T 6
9.8%
W 5
8.2%
P 5
8.2%
D 3
 
4.9%
B 3
 
4.9%
I 3
 
4.9%
Other values (8) 12
19.7%
Other Punctuation
ValueCountFrequency (%)
. 11
55.0%
, 7
35.0%
' 1
 
5.0%
/ 1
 
5.0%
Space Separator
ValueCountFrequency (%)
251
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Decimal Number
ValueCountFrequency (%)
1 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1274
82.3%
Common 274
 
17.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 155
12.2%
t 111
 
8.7%
r 101
 
7.9%
a 95
 
7.5%
n 94
 
7.4%
o 90
 
7.1%
i 83
 
6.5%
s 64
 
5.0%
d 59
 
4.6%
h 40
 
3.1%
Other values (32) 382
30.0%
Common
ValueCountFrequency (%)
251
91.6%
. 11
 
4.0%
, 7
 
2.6%
- 2
 
0.7%
1 1
 
0.4%
' 1
 
0.4%
/ 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1548
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
251
16.2%
e 155
 
10.0%
t 111
 
7.2%
r 101
 
6.5%
a 95
 
6.1%
n 94
 
6.1%
o 90
 
5.8%
i 83
 
5.4%
s 64
 
4.1%
d 59
 
3.8%
Other values (39) 445
28.7%

q40_r1_c1_2
Text

MISSING 

Distinct170
Distinct (%)44.5%
Missing618
Missing (%)61.8%
Memory size47.9 KiB
2023-12-09T22:16:14.663288image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length63
Median length39
Mean length19.33769634
Min length3

Characters and Unicode

Total characters7387
Distinct characters66
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique103 ?
Unique (%)27.0%

Sample

1st rowThird Street Music School Settlement
2nd rowMusic and the Brain
3rd rowRosie's Theater Kids
4th rowThird Street Music School Settlement
5th rowHenry Street Settlement
ValueCountFrequency (%)
arts 46
 
4.1%
of 40
 
3.5%
other 33
 
2.9%
museum 30
 
2.6%
art 25
 
2.2%
in 23
 
2.0%
music 23
 
2.0%
the 22
 
1.9%
theatre 20
 
1.8%
center 19
 
1.7%
Other values (269) 853
75.2%
2023-12-09T22:16:15.207492image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
752
 
10.2%
e 611
 
8.3%
r 513
 
6.9%
t 476
 
6.4%
o 458
 
6.2%
n 443
 
6.0%
a 420
 
5.7%
i 416
 
5.6%
s 281
 
3.8%
l 245
 
3.3%
Other values (56) 2772
37.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 5272
71.4%
Uppercase Letter 1272
 
17.2%
Space Separator 752
 
10.2%
Other Punctuation 49
 
0.7%
Decimal Number 22
 
0.3%
Close Punctuation 8
 
0.1%
Open Punctuation 8
 
0.1%
Dash Punctuation 4
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 611
11.6%
r 513
9.7%
t 476
9.0%
o 458
 
8.7%
n 443
 
8.4%
a 420
 
8.0%
i 416
 
7.9%
s 281
 
5.3%
l 245
 
4.6%
u 241
 
4.6%
Other values (16) 1168
22.2%
Uppercase Letter
ValueCountFrequency (%)
A 179
14.1%
M 118
 
9.3%
C 114
 
9.0%
T 104
 
8.2%
S 103
 
8.1%
E 86
 
6.8%
P 72
 
5.7%
B 69
 
5.4%
H 52
 
4.1%
R 50
 
3.9%
Other values (15) 325
25.6%
Other Punctuation
ValueCountFrequency (%)
. 18
36.7%
& 11
22.4%
' 8
16.3%
/ 7
 
14.3%
, 2
 
4.1%
: 2
 
4.1%
! 1
 
2.0%
Decimal Number
ValueCountFrequency (%)
2 11
50.0%
9 6
27.3%
4 3
 
13.6%
1 2
 
9.1%
Space Separator
ValueCountFrequency (%)
752
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 6544
88.6%
Common 843
 
11.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 611
 
9.3%
r 513
 
7.8%
t 476
 
7.3%
o 458
 
7.0%
n 443
 
6.8%
a 420
 
6.4%
i 416
 
6.4%
s 281
 
4.3%
l 245
 
3.7%
u 241
 
3.7%
Other values (41) 2440
37.3%
Common
ValueCountFrequency (%)
752
89.2%
. 18
 
2.1%
& 11
 
1.3%
2 11
 
1.3%
) 8
 
0.9%
' 8
 
0.9%
( 8
 
0.9%
/ 7
 
0.8%
9 6
 
0.7%
- 4
 
0.5%
Other values (5) 10
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7387
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
752
 
10.2%
e 611
 
8.3%
r 513
 
6.9%
t 476
 
6.4%
o 458
 
6.2%
n 443
 
6.0%
a 420
 
5.7%
i 416
 
5.6%
s 281
 
3.8%
l 245
 
3.3%
Other values (56) 2772
37.5%

q40_r1_c2_2
Text

MISSING 

Distinct32
Distinct (%)97.0%
Missing967
Missing (%)96.7%
Memory size32.8 KiB
2023-12-09T22:16:15.544997image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length43
Median length23
Mean length17.75757576
Min length6

Characters and Unicode

Total characters586
Distinct characters48
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)93.9%

Sample

1st rowWhitney Museum
2nd rowParson
3rd rowUnited Arts Experience
4th rowThe Leadership Program
5th rowThe Leadership Program
ValueCountFrequency (%)
the 3
 
3.4%
arts 3
 
3.4%
leadership 3
 
3.4%
life 2
 
2.3%
art 2
 
2.3%
of 2
 
2.3%
foundation 2
 
2.3%
song 2
 
2.3%
program 2
 
2.3%
hills 1
 
1.1%
Other values (65) 65
74.7%
2023-12-09T22:16:16.030249image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 60
 
10.2%
54
 
9.2%
r 44
 
7.5%
i 40
 
6.8%
a 38
 
6.5%
o 33
 
5.6%
s 31
 
5.3%
n 27
 
4.6%
t 27
 
4.6%
l 25
 
4.3%
Other values (38) 207
35.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 437
74.6%
Uppercase Letter 92
 
15.7%
Space Separator 54
 
9.2%
Other Punctuation 3
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 60
13.7%
r 44
10.1%
i 40
9.2%
a 38
 
8.7%
o 33
 
7.6%
s 31
 
7.1%
n 27
 
6.2%
t 27
 
6.2%
l 25
 
5.7%
h 16
 
3.7%
Other values (15) 96
22.0%
Uppercase Letter
ValueCountFrequency (%)
L 12
13.0%
C 11
12.0%
A 9
9.8%
T 9
9.8%
S 8
8.7%
P 7
 
7.6%
M 5
 
5.4%
B 4
 
4.3%
U 4
 
4.3%
H 4
 
4.3%
Other values (10) 19
20.7%
Other Punctuation
ValueCountFrequency (%)
, 2
66.7%
. 1
33.3%
Space Separator
ValueCountFrequency (%)
54
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 529
90.3%
Common 57
 
9.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 60
 
11.3%
r 44
 
8.3%
i 40
 
7.6%
a 38
 
7.2%
o 33
 
6.2%
s 31
 
5.9%
n 27
 
5.1%
t 27
 
5.1%
l 25
 
4.7%
h 16
 
3.0%
Other values (35) 188
35.5%
Common
ValueCountFrequency (%)
54
94.7%
, 2
 
3.5%
. 1
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 586
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 60
 
10.2%
54
 
9.2%
r 44
 
7.5%
i 40
 
6.8%
a 38
 
6.5%
o 33
 
5.6%
s 31
 
5.3%
n 27
 
4.6%
t 27
 
4.6%
l 25
 
4.3%
Other values (38) 207
35.3%

q40_r1_c3_2
Text

MISSING 

Distinct6
Distinct (%)1.6%
Missing621
Missing (%)62.1%
Memory size43.3 KiB
2023-12-09T22:16:16.219165image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length11
Median length10
Mean length7.234828496
Min length5

Characters and Unicode

Total characters2742
Distinct characters22
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowMusic
2nd rowMusic
3rd rowTheater
4th rowMusic
5th rowVisual Arts
ValueCountFrequency (%)
visual 100
20.9%
arts 100
20.9%
theater 96
20.0%
music 92
19.2%
dance 63
13.2%
other 17
 
3.5%
film/media 11
 
2.3%
2023-12-09T22:16:16.532706image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 292
10.6%
e 283
10.3%
a 270
 
9.8%
i 214
 
7.8%
r 213
 
7.8%
t 213
 
7.8%
u 192
 
7.0%
c 155
 
5.7%
h 113
 
4.1%
l 111
 
4.0%
Other values (12) 686
25.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2141
78.1%
Uppercase Letter 490
 
17.9%
Space Separator 100
 
3.6%
Other Punctuation 11
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 292
13.6%
e 283
13.2%
a 270
12.6%
i 214
10.0%
r 213
9.9%
t 213
9.9%
u 192
9.0%
c 155
7.2%
h 113
 
5.3%
l 111
 
5.2%
Other values (3) 85
 
4.0%
Uppercase Letter
ValueCountFrequency (%)
M 103
21.0%
V 100
20.4%
A 100
20.4%
T 96
19.6%
D 63
12.9%
O 17
 
3.5%
F 11
 
2.2%
Space Separator
ValueCountFrequency (%)
100
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2631
96.0%
Common 111
 
4.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
s 292
11.1%
e 283
10.8%
a 270
10.3%
i 214
 
8.1%
r 213
 
8.1%
t 213
 
8.1%
u 192
 
7.3%
c 155
 
5.9%
h 113
 
4.3%
l 111
 
4.2%
Other values (10) 575
21.9%
Common
ValueCountFrequency (%)
100
90.1%
/ 11
 
9.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2742
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
s 292
10.6%
e 283
10.3%
a 270
 
9.8%
i 214
 
7.8%
r 213
 
7.8%
t 213
 
7.8%
u 192
 
7.0%
c 155
 
5.7%
h 113
 
4.1%
l 111
 
4.0%
Other values (12) 686
25.0%

q40_r1_c4_2
Text

MISSING 

Distinct4
Distinct (%)1.1%
Missing624
Missing (%)62.4%
Memory size53.9 KiB
2023-12-09T22:16:16.737727image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length42
Median length42
Mean length36.31914894
Min length24

Characters and Unicode

Total characters13656
Distinct characters32
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowResidency (direct instruction to students)
2nd rowTeacher Professional Development
3rd rowResidency (direct instruction to students)
4th rowResidency (direct instruction to students)
5th rowResidency (direct instruction to students)
ValueCountFrequency (%)
residency 233
14.2%
direct 233
14.2%
instruction 233
14.2%
to 233
14.2%
students 233
14.2%
in-school 66
 
4.0%
student 66
 
4.0%
workshops 66
 
4.0%
arts 47
 
2.9%
related 47
 
2.9%
Other values (5) 184
11.2%
2023-12-09T22:16:17.076029image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 1654
12.1%
e 1319
9.7%
s 1284
9.4%
1265
9.3%
n 1124
8.2%
i 1056
 
7.7%
d 859
 
6.3%
o 820
 
6.0%
c 795
 
5.8%
r 686
 
5.0%
Other values (22) 2794
20.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 11150
81.6%
Space Separator 1265
 
9.3%
Uppercase Letter 709
 
5.2%
Open Punctuation 233
 
1.7%
Close Punctuation 233
 
1.7%
Dash Punctuation 66
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 1654
14.8%
e 1319
11.8%
s 1284
11.5%
n 1124
10.1%
i 1056
9.5%
d 859
7.7%
o 820
7.4%
c 795
7.1%
r 686
6.2%
u 532
 
4.8%
Other values (9) 1021
9.2%
Uppercase Letter
ValueCountFrequency (%)
R 280
39.5%
T 77
 
10.9%
W 66
 
9.3%
S 66
 
9.3%
I 66
 
9.3%
A 47
 
6.6%
F 47
 
6.6%
P 30
 
4.2%
D 30
 
4.2%
Space Separator
ValueCountFrequency (%)
1265
100.0%
Open Punctuation
ValueCountFrequency (%)
( 233
100.0%
Close Punctuation
ValueCountFrequency (%)
) 233
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 66
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 11859
86.8%
Common 1797
 
13.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 1654
13.9%
e 1319
11.1%
s 1284
10.8%
n 1124
9.5%
i 1056
8.9%
d 859
7.2%
o 820
6.9%
c 795
6.7%
r 686
 
5.8%
u 532
 
4.5%
Other values (18) 1730
14.6%
Common
ValueCountFrequency (%)
1265
70.4%
( 233
 
13.0%
) 233
 
13.0%
- 66
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13656
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 1654
12.1%
e 1319
9.7%
s 1284
9.4%
1265
9.3%
n 1124
8.2%
i 1056
 
7.7%
d 859
 
6.3%
o 820
 
6.0%
c 795
 
5.8%
r 686
 
5.0%
Other values (22) 2794
20.5%

q40_r1_c5_2
Text

MISSING 

Distinct5
Distinct (%)1.3%
Missing627
Missing (%)62.7%
Memory size40.8 KiB
2023-12-09T22:16:17.195716image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters373
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)0.5%

Sample

1st row4
2nd row5
3rd row5
4th row5
5th row5
ValueCountFrequency (%)
5 327
87.7%
4 34
 
9.1%
3 10
 
2.7%
2 1
 
0.3%
1 1
 
0.3%
2023-12-09T22:16:17.430065image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 327
87.7%
4 34
 
9.1%
3 10
 
2.7%
2 1
 
0.3%
1 1
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 373
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 327
87.7%
4 34
 
9.1%
3 10
 
2.7%
2 1
 
0.3%
1 1
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
Common 373
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 327
87.7%
4 34
 
9.1%
3 10
 
2.7%
2 1
 
0.3%
1 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 373
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 327
87.7%
4 34
 
9.1%
3 10
 
2.7%
2 1
 
0.3%
1 1
 
0.3%

q40_r1_c6_2
Text

MISSING 

Distinct137
Distinct (%)37.5%
Missing635
Missing (%)63.5%
Memory size41.1 KiB
2023-12-09T22:16:17.823531image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.394520548
Min length1

Characters and Unicode

Total characters874
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique83 ?
Unique (%)22.7%

Sample

1st row183
2nd row200
3rd row77
4th row300
5th row45
ValueCountFrequency (%)
30 20
 
5.5%
100 18
 
4.9%
20 17
 
4.7%
150 15
 
4.1%
60 13
 
3.6%
200 12
 
3.3%
25 11
 
3.0%
50 11
 
3.0%
40 10
 
2.7%
0 9
 
2.5%
Other values (127) 229
62.7%
2023-12-09T22:16:18.369281image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 257
29.4%
1 132
15.1%
5 110
12.6%
2 107
12.2%
4 64
 
7.3%
3 63
 
7.2%
8 41
 
4.7%
6 40
 
4.6%
7 38
 
4.3%
9 22
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 874
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 257
29.4%
1 132
15.1%
5 110
12.6%
2 107
12.2%
4 64
 
7.3%
3 63
 
7.2%
8 41
 
4.7%
6 40
 
4.6%
7 38
 
4.3%
9 22
 
2.5%

Most occurring scripts

ValueCountFrequency (%)
Common 874
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 257
29.4%
1 132
15.1%
5 110
12.6%
2 107
12.2%
4 64
 
7.3%
3 63
 
7.2%
8 41
 
4.7%
6 40
 
4.6%
7 38
 
4.3%
9 22
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 874
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 257
29.4%
1 132
15.1%
5 110
12.6%
2 107
12.2%
4 64
 
7.3%
3 63
 
7.2%
8 41
 
4.7%
6 40
 
4.6%
7 38
 
4.3%
9 22
 
2.5%

q40_r1_c7_2
Text

MISSING 

Distinct55
Distinct (%)15.2%
Missing639
Missing (%)63.9%
Memory size40.8 KiB
2023-12-09T22:16:18.631354image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length1.648199446
Min length1

Characters and Unicode

Total characters595
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)6.6%

Sample

1st row30
2nd row0
3rd row10
4th row30
5th row17
ValueCountFrequency (%)
10 36
 
10.0%
1 33
 
9.1%
2 28
 
7.8%
20 21
 
5.8%
30 21
 
5.8%
6 17
 
4.7%
12 16
 
4.4%
40 13
 
3.6%
5 12
 
3.3%
15 12
 
3.3%
Other values (45) 152
42.1%
2023-12-09T22:16:19.025007image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 139
23.4%
0 135
22.7%
2 93
15.6%
5 57
9.6%
3 43
 
7.2%
6 43
 
7.2%
4 38
 
6.4%
8 25
 
4.2%
7 14
 
2.4%
9 8
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 595
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 139
23.4%
0 135
22.7%
2 93
15.6%
5 57
9.6%
3 43
 
7.2%
6 43
 
7.2%
4 38
 
6.4%
8 25
 
4.2%
7 14
 
2.4%
9 8
 
1.3%

Most occurring scripts

ValueCountFrequency (%)
Common 595
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 139
23.4%
0 135
22.7%
2 93
15.6%
5 57
9.6%
3 43
 
7.2%
6 43
 
7.2%
4 38
 
6.4%
8 25
 
4.2%
7 14
 
2.4%
9 8
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 595
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 139
23.4%
0 135
22.7%
2 93
15.6%
5 57
9.6%
3 43
 
7.2%
6 43
 
7.2%
4 38
 
6.4%
8 25
 
4.2%
7 14
 
2.4%
9 8
 
1.3%

q40_r1_c8_2
Text

MISSING 

Distinct3
Distinct (%)0.8%
Missing628
Missing (%)62.8%
Memory size41.9 KiB
2023-12-09T22:16:19.173999image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length9
Median length3
Mean length3.897849462
Min length2

Characters and Unicode

Total characters1450
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowUncertain
2nd rowYes
3rd rowYes
4th rowYes
5th rowYes
ValueCountFrequency (%)
yes 314
84.4%
uncertain 56
 
15.1%
no 2
 
0.5%
2023-12-09T22:16:19.452700image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 370
25.5%
Y 314
21.7%
s 314
21.7%
n 112
 
7.7%
U 56
 
3.9%
c 56
 
3.9%
r 56
 
3.9%
t 56
 
3.9%
a 56
 
3.9%
i 56
 
3.9%
Other values (2) 4
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1078
74.3%
Uppercase Letter 372
 
25.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 370
34.3%
s 314
29.1%
n 112
 
10.4%
c 56
 
5.2%
r 56
 
5.2%
t 56
 
5.2%
a 56
 
5.2%
i 56
 
5.2%
o 2
 
0.2%
Uppercase Letter
ValueCountFrequency (%)
Y 314
84.4%
U 56
 
15.1%
N 2
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
Latin 1450
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 370
25.5%
Y 314
21.7%
s 314
21.7%
n 112
 
7.7%
U 56
 
3.9%
c 56
 
3.9%
r 56
 
3.9%
t 56
 
3.9%
a 56
 
3.9%
i 56
 
3.9%
Other values (2) 4
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1450
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 370
25.5%
Y 314
21.7%
s 314
21.7%
n 112
 
7.7%
U 56
 
3.9%
c 56
 
3.9%
r 56
 
3.9%
t 56
 
3.9%
a 56
 
3.9%
i 56
 
3.9%
Other values (2) 4
 
0.3%

q40_r1_c10_2
Text

MISSING 

Distinct8
Distinct (%)100.0%
Missing992
Missing (%)99.2%
Memory size31.8 KiB
2023-12-09T22:16:19.682067image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length60
Median length26.5
Mean length24.75
Min length6

Characters and Unicode

Total characters198
Distinct characters31
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)100.0%

Sample

1st rowschool merger
2nd rowFunding and credit for Arts compliance
3rd rowlimited space
4th rowThis is the end of year 3 of contract with the organization.
5th rowPending funding
ValueCountFrequency (%)
funding 2
 
6.1%
the 2
 
6.1%
arts 2
 
6.1%
of 2
 
6.1%
and 2
 
6.1%
limited 1
 
3.0%
dance 1
 
3.0%
visual 1
 
3.0%
provided 1
 
3.0%
compliance 1
 
3.0%
Other values (18) 18
54.5%
2023-12-09T22:16:20.051001image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
25
12.6%
e 18
 
9.1%
n 15
 
7.6%
i 15
 
7.6%
d 13
 
6.6%
t 12
 
6.1%
r 11
 
5.6%
o 11
 
5.6%
a 10
 
5.1%
s 9
 
4.5%
Other values (21) 59
29.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 162
81.8%
Space Separator 25
 
12.6%
Uppercase Letter 7
 
3.5%
Other Punctuation 3
 
1.5%
Decimal Number 1
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 18
11.1%
n 15
 
9.3%
i 15
 
9.3%
d 13
 
8.0%
t 12
 
7.4%
r 11
 
6.8%
o 11
 
6.8%
a 10
 
6.2%
s 9
 
5.6%
c 9
 
5.6%
Other values (12) 39
24.1%
Uppercase Letter
ValueCountFrequency (%)
P 2
28.6%
A 2
28.6%
T 1
14.3%
F 1
14.3%
V 1
14.3%
Other Punctuation
ValueCountFrequency (%)
, 2
66.7%
. 1
33.3%
Space Separator
ValueCountFrequency (%)
25
100.0%
Decimal Number
ValueCountFrequency (%)
3 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 169
85.4%
Common 29
 
14.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 18
 
10.7%
n 15
 
8.9%
i 15
 
8.9%
d 13
 
7.7%
t 12
 
7.1%
r 11
 
6.5%
o 11
 
6.5%
a 10
 
5.9%
s 9
 
5.3%
c 9
 
5.3%
Other values (17) 46
27.2%
Common
ValueCountFrequency (%)
25
86.2%
, 2
 
6.9%
3 1
 
3.4%
. 1
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 198
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
25
12.6%
e 18
 
9.1%
n 15
 
7.6%
i 15
 
7.6%
d 13
 
6.6%
t 12
 
6.1%
r 11
 
5.6%
o 11
 
5.6%
a 10
 
5.1%
s 9
 
4.5%
Other values (21) 59
29.8%

q40_r1_c1_3
Text

MISSING 

Distinct147
Distinct (%)59.0%
Missing751
Missing (%)75.1%
Memory size42.5 KiB
2023-12-09T22:16:20.433843image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length59
Median length35
Mean length20.51004016
Min length3

Characters and Unicode

Total characters5107
Distinct characters67
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique109 ?
Unique (%)43.8%

Sample

1st rowMark DeGarmo
2nd rowSEA Theater
3rd rowDancing Classrooms
4th rowTake Two Film Academy
5th rowRepertorio Español
ValueCountFrequency (%)
arts 39
 
4.9%
museum 27
 
3.4%
of 25
 
3.2%
other 19
 
2.4%
center 18
 
2.3%
14
 
1.8%
the 14
 
1.8%
art 13
 
1.6%
learning 12
 
1.5%
theater 12
 
1.5%
Other values (245) 598
75.6%
2023-12-09T22:16:20.990473image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
542
 
10.6%
e 425
 
8.3%
r 371
 
7.3%
n 314
 
6.1%
a 307
 
6.0%
t 305
 
6.0%
o 291
 
5.7%
i 262
 
5.1%
s 196
 
3.8%
u 190
 
3.7%
Other values (57) 1904
37.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3669
71.8%
Uppercase Letter 826
 
16.2%
Space Separator 542
 
10.6%
Other Punctuation 32
 
0.6%
Open Punctuation 12
 
0.2%
Close Punctuation 12
 
0.2%
Decimal Number 12
 
0.2%
Math Symbol 1
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 425
11.6%
r 371
10.1%
n 314
 
8.6%
a 307
 
8.4%
t 305
 
8.3%
o 291
 
7.9%
i 262
 
7.1%
s 196
 
5.3%
u 190
 
5.2%
l 163
 
4.4%
Other values (17) 845
23.0%
Uppercase Letter
ValueCountFrequency (%)
A 117
14.2%
C 99
12.0%
M 74
 
9.0%
T 66
 
8.0%
S 63
 
7.6%
E 54
 
6.5%
P 52
 
6.3%
H 43
 
5.2%
L 30
 
3.6%
R 29
 
3.5%
Other values (15) 199
24.1%
Other Punctuation
ValueCountFrequency (%)
& 13
40.6%
' 10
31.2%
. 4
 
12.5%
/ 3
 
9.4%
, 1
 
3.1%
: 1
 
3.1%
Decimal Number
ValueCountFrequency (%)
2 6
50.0%
1 3
25.0%
9 2
 
16.7%
4 1
 
8.3%
Space Separator
ValueCountFrequency (%)
542
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4495
88.0%
Common 612
 
12.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 425
 
9.5%
r 371
 
8.3%
n 314
 
7.0%
a 307
 
6.8%
t 305
 
6.8%
o 291
 
6.5%
i 262
 
5.8%
s 196
 
4.4%
u 190
 
4.2%
l 163
 
3.6%
Other values (42) 1671
37.2%
Common
ValueCountFrequency (%)
542
88.6%
& 13
 
2.1%
( 12
 
2.0%
) 12
 
2.0%
' 10
 
1.6%
2 6
 
1.0%
. 4
 
0.7%
/ 3
 
0.5%
1 3
 
0.5%
9 2
 
0.3%
Other values (5) 5
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5106
> 99.9%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
542
 
10.6%
e 425
 
8.3%
r 371
 
7.3%
n 314
 
6.1%
a 307
 
6.0%
t 305
 
6.0%
o 291
 
5.7%
i 262
 
5.1%
s 196
 
3.8%
u 190
 
3.7%
Other values (56) 1903
37.3%
None
ValueCountFrequency (%)
ñ 1
100.0%

q40_r1_c2_3
Text

MISSING 

Distinct18
Distinct (%)94.7%
Missing981
Missing (%)98.1%
Memory size32.2 KiB
2023-12-09T22:16:21.273070image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length34
Median length19
Mean length17.52631579
Min length4

Characters and Unicode

Total characters333
Distinct characters47
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)89.5%

Sample

1st rowPossibility Project
2nd rowUnited Arts Experience
3rd rowThe Leadership Program
4th rowThe Leadership Program
5th rowJessica Ruhlin
ValueCountFrequency (%)
the 2
 
4.3%
project 2
 
4.3%
leadership 2
 
4.3%
program 2
 
4.3%
jessica 1
 
2.1%
freearts 1
 
2.1%
tech 1
 
2.1%
in 1
 
2.1%
schools 1
 
2.1%
initiative 1
 
2.1%
Other values (33) 33
70.2%
2023-12-09T22:16:21.695123image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 36
 
10.8%
29
 
8.7%
r 27
 
8.1%
i 21
 
6.3%
t 20
 
6.0%
s 20
 
6.0%
a 19
 
5.7%
n 16
 
4.8%
o 15
 
4.5%
h 10
 
3.0%
Other values (37) 120
36.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 252
75.7%
Uppercase Letter 50
 
15.0%
Space Separator 29
 
8.7%
Other Punctuation 2
 
0.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 36
14.3%
r 27
10.7%
i 21
 
8.3%
t 20
 
7.9%
s 20
 
7.9%
a 19
 
7.5%
n 16
 
6.3%
o 15
 
6.0%
h 10
 
4.0%
c 9
 
3.6%
Other values (15) 59
23.4%
Uppercase Letter
ValueCountFrequency (%)
T 6
12.0%
S 6
12.0%
P 6
12.0%
A 5
 
10.0%
W 3
 
6.0%
M 3
 
6.0%
I 2
 
4.0%
H 2
 
4.0%
R 2
 
4.0%
U 2
 
4.0%
Other values (9) 13
26.0%
Other Punctuation
ValueCountFrequency (%)
. 1
50.0%
' 1
50.0%
Space Separator
ValueCountFrequency (%)
29
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 302
90.7%
Common 31
 
9.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 36
 
11.9%
r 27
 
8.9%
i 21
 
7.0%
t 20
 
6.6%
s 20
 
6.6%
a 19
 
6.3%
n 16
 
5.3%
o 15
 
5.0%
h 10
 
3.3%
c 9
 
3.0%
Other values (34) 109
36.1%
Common
ValueCountFrequency (%)
29
93.5%
. 1
 
3.2%
' 1
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 333
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 36
 
10.8%
29
 
8.7%
r 27
 
8.1%
i 21
 
6.3%
t 20
 
6.0%
s 20
 
6.0%
a 19
 
5.7%
n 16
 
4.8%
o 15
 
4.5%
h 10
 
3.0%
Other values (37) 120
36.0%

q40_r1_c3_3
Text

MISSING 

Distinct6
Distinct (%)2.4%
Missing753
Missing (%)75.3%
Memory size39.2 KiB
2023-12-09T22:16:21.883380image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length11
Median length10
Mean length7.477732794
Min length5

Characters and Unicode

Total characters1847
Distinct characters22
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowDance
2nd rowTheater
3rd rowDance
4th rowFilm/Media
5th rowTheater
ValueCountFrequency (%)
visual 75
23.3%
arts 75
23.3%
music 53
16.5%
theater 51
15.8%
dance 41
12.7%
other 15
 
4.7%
film/media 12
 
3.7%
2023-12-09T22:16:22.198402image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 203
11.0%
a 179
 
9.7%
e 170
 
9.2%
i 152
 
8.2%
t 141
 
7.6%
r 141
 
7.6%
u 128
 
6.9%
c 94
 
5.1%
l 87
 
4.7%
V 75
 
4.1%
Other values (12) 477
25.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1426
77.2%
Uppercase Letter 334
 
18.1%
Space Separator 75
 
4.1%
Other Punctuation 12
 
0.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 203
14.2%
a 179
12.6%
e 170
11.9%
i 152
10.7%
t 141
9.9%
r 141
9.9%
u 128
9.0%
c 94
6.6%
l 87
6.1%
h 66
 
4.6%
Other values (3) 65
 
4.6%
Uppercase Letter
ValueCountFrequency (%)
V 75
22.5%
A 75
22.5%
M 65
19.5%
T 51
15.3%
D 41
12.3%
O 15
 
4.5%
F 12
 
3.6%
Space Separator
ValueCountFrequency (%)
75
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1760
95.3%
Common 87
 
4.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
s 203
11.5%
a 179
10.2%
e 170
9.7%
i 152
 
8.6%
t 141
 
8.0%
r 141
 
8.0%
u 128
 
7.3%
c 94
 
5.3%
l 87
 
4.9%
V 75
 
4.3%
Other values (10) 390
22.2%
Common
ValueCountFrequency (%)
75
86.2%
/ 12
 
13.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1847
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
s 203
11.0%
a 179
 
9.7%
e 170
 
9.2%
i 152
 
8.2%
t 141
 
7.6%
r 141
 
7.6%
u 128
 
6.9%
c 94
 
5.1%
l 87
 
4.7%
V 75
 
4.1%
Other values (12) 477
25.8%

q40_r1_c4_3
Text

MISSING 

Distinct4
Distinct (%)1.6%
Missing756
Missing (%)75.6%
Memory size45.8 KiB
2023-12-09T22:16:22.407956image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length42
Median length42
Mean length35.39754098
Min length24

Characters and Unicode

Total characters8637
Distinct characters32
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowResidency (direct instruction to students)
2nd rowArts Related Field Trips
3rd rowResidency (direct instruction to students)
4th rowResidency (direct instruction to students)
5th rowResidency (direct instruction to students)
ValueCountFrequency (%)
residency 139
13.2%
direct 139
13.2%
instruction 139
13.2%
to 139
13.2%
students 139
13.2%
in-school 45
 
4.3%
student 45
 
4.3%
workshops 45
 
4.3%
arts 42
 
4.0%
related 42
 
4.0%
Other values (5) 138
13.1%
2023-12-09T22:16:22.758434image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 1026
11.9%
e 835
9.7%
s 811
9.4%
808
9.4%
n 682
 
7.9%
i 658
 
7.6%
d 546
 
6.3%
o 512
 
5.9%
c 480
 
5.6%
r 443
 
5.1%
Other values (22) 1836
21.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 7010
81.2%
Space Separator 808
 
9.4%
Uppercase Letter 496
 
5.7%
Open Punctuation 139
 
1.6%
Close Punctuation 139
 
1.6%
Dash Punctuation 45
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 1026
14.6%
e 835
11.9%
s 811
11.6%
n 682
9.7%
i 658
9.4%
d 546
7.8%
o 512
7.3%
c 480
6.8%
r 443
6.3%
u 323
 
4.6%
Other values (9) 694
9.9%
Uppercase Letter
ValueCountFrequency (%)
R 181
36.5%
T 60
 
12.1%
W 45
 
9.1%
S 45
 
9.1%
I 45
 
9.1%
A 42
 
8.5%
F 42
 
8.5%
P 18
 
3.6%
D 18
 
3.6%
Space Separator
ValueCountFrequency (%)
808
100.0%
Open Punctuation
ValueCountFrequency (%)
( 139
100.0%
Close Punctuation
ValueCountFrequency (%)
) 139
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 45
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 7506
86.9%
Common 1131
 
13.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 1026
13.7%
e 835
11.1%
s 811
10.8%
n 682
9.1%
i 658
8.8%
d 546
7.3%
o 512
6.8%
c 480
6.4%
r 443
 
5.9%
u 323
 
4.3%
Other values (18) 1190
15.9%
Common
ValueCountFrequency (%)
808
71.4%
( 139
 
12.3%
) 139
 
12.3%
- 45
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8637
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 1026
11.9%
e 835
9.7%
s 811
9.4%
808
9.4%
n 682
 
7.9%
i 658
 
7.6%
d 546
 
6.3%
o 512
 
5.9%
c 480
 
5.6%
r 443
 
5.1%
Other values (22) 1836
21.3%

q40_r1_c5_3
Text

MISSING 

Distinct4
Distinct (%)1.6%
Missing755
Missing (%)75.5%
Memory size37.6 KiB
2023-12-09T22:16:22.877091image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters245
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.4%

Sample

1st row4
2nd row5
3rd row5
4th row3
5th row5
ValueCountFrequency (%)
5 211
86.1%
4 27
 
11.0%
3 6
 
2.4%
1 1
 
0.4%
2023-12-09T22:16:23.102454image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 211
86.1%
4 27
 
11.0%
3 6
 
2.4%
1 1
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 245
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 211
86.1%
4 27
 
11.0%
3 6
 
2.4%
1 1
 
0.4%

Most occurring scripts

ValueCountFrequency (%)
Common 245
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 211
86.1%
4 27
 
11.0%
3 6
 
2.4%
1 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 245
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 211
86.1%
4 27
 
11.0%
3 6
 
2.4%
1 1
 
0.4%

q40_r1_c6_3
Text

MISSING 

Distinct112
Distinct (%)46.5%
Missing759
Missing (%)75.9%
Memory size37.8 KiB
2023-12-09T22:16:23.450273image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length4
Median length2
Mean length2.394190871
Min length1

Characters and Unicode

Total characters577
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique74 ?
Unique (%)30.7%

Sample

1st row35
2nd row200
3rd row77
4th row50
5th row58
ValueCountFrequency (%)
100 20
 
8.3%
20 10
 
4.1%
50 10
 
4.1%
150 9
 
3.7%
10 8
 
3.3%
30 8
 
3.3%
75 7
 
2.9%
60 6
 
2.5%
15 6
 
2.5%
400 5
 
2.1%
Other values (102) 152
63.1%
2023-12-09T22:16:23.949406image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 164
28.4%
1 95
16.5%
5 74
12.8%
2 60
 
10.4%
3 45
 
7.8%
4 37
 
6.4%
6 35
 
6.1%
8 26
 
4.5%
9 22
 
3.8%
7 19
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 577
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 164
28.4%
1 95
16.5%
5 74
12.8%
2 60
 
10.4%
3 45
 
7.8%
4 37
 
6.4%
6 35
 
6.1%
8 26
 
4.5%
9 22
 
3.8%
7 19
 
3.3%

Most occurring scripts

ValueCountFrequency (%)
Common 577
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 164
28.4%
1 95
16.5%
5 74
12.8%
2 60
 
10.4%
3 45
 
7.8%
4 37
 
6.4%
6 35
 
6.1%
8 26
 
4.5%
9 22
 
3.8%
7 19
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 577
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 164
28.4%
1 95
16.5%
5 74
12.8%
2 60
 
10.4%
3 45
 
7.8%
4 37
 
6.4%
6 35
 
6.1%
8 26
 
4.5%
9 22
 
3.8%
7 19
 
3.3%

q40_r1_c7_3
Text

MISSING 

Distinct42
Distinct (%)17.6%
Missing761
Missing (%)76.1%
Memory size37.6 KiB
2023-12-09T22:16:24.192102image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length1.589958159
Min length1

Characters and Unicode

Total characters380
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)6.3%

Sample

1st row8
2nd row3
3rd row10
4th row15
5th row10
ValueCountFrequency (%)
1 26
 
10.9%
10 24
 
10.0%
2 23
 
9.6%
30 19
 
7.9%
20 14
 
5.9%
3 11
 
4.6%
6 11
 
4.6%
15 10
 
4.2%
4 8
 
3.3%
8 8
 
3.3%
Other values (32) 85
35.6%
2023-12-09T22:16:24.565109image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 92
24.2%
1 88
23.2%
2 59
15.5%
3 34
 
8.9%
5 33
 
8.7%
4 24
 
6.3%
6 21
 
5.5%
8 12
 
3.2%
7 10
 
2.6%
9 7
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 380
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 92
24.2%
1 88
23.2%
2 59
15.5%
3 34
 
8.9%
5 33
 
8.7%
4 24
 
6.3%
6 21
 
5.5%
8 12
 
3.2%
7 10
 
2.6%
9 7
 
1.8%

Most occurring scripts

ValueCountFrequency (%)
Common 380
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 92
24.2%
1 88
23.2%
2 59
15.5%
3 34
 
8.9%
5 33
 
8.7%
4 24
 
6.3%
6 21
 
5.5%
8 12
 
3.2%
7 10
 
2.6%
9 7
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 380
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 92
24.2%
1 88
23.2%
2 59
15.5%
3 34
 
8.9%
5 33
 
8.7%
4 24
 
6.3%
6 21
 
5.5%
8 12
 
3.2%
7 10
 
2.6%
9 7
 
1.8%

q40_r1_c8_3
Text

MISSING 

Distinct3
Distinct (%)1.2%
Missing758
Missing (%)75.8%
Memory size38.2 KiB
2023-12-09T22:16:24.714002image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length9
Median length3
Mean length3.884297521
Min length2

Characters and Unicode

Total characters940
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowUncertain
2nd rowYes
3rd rowYes
4th rowUncertain
5th rowYes
ValueCountFrequency (%)
yes 204
84.3%
uncertain 36
 
14.9%
no 2
 
0.8%
2023-12-09T22:16:24.987293image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 240
25.5%
Y 204
21.7%
s 204
21.7%
n 72
 
7.7%
U 36
 
3.8%
c 36
 
3.8%
r 36
 
3.8%
t 36
 
3.8%
a 36
 
3.8%
i 36
 
3.8%
Other values (2) 4
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 698
74.3%
Uppercase Letter 242
 
25.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 240
34.4%
s 204
29.2%
n 72
 
10.3%
c 36
 
5.2%
r 36
 
5.2%
t 36
 
5.2%
a 36
 
5.2%
i 36
 
5.2%
o 2
 
0.3%
Uppercase Letter
ValueCountFrequency (%)
Y 204
84.3%
U 36
 
14.9%
N 2
 
0.8%

Most occurring scripts

ValueCountFrequency (%)
Latin 940
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 240
25.5%
Y 204
21.7%
s 204
21.7%
n 72
 
7.7%
U 36
 
3.8%
c 36
 
3.8%
r 36
 
3.8%
t 36
 
3.8%
a 36
 
3.8%
i 36
 
3.8%
Other values (2) 4
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 940
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 240
25.5%
Y 204
21.7%
s 204
21.7%
n 72
 
7.7%
U 36
 
3.8%
c 36
 
3.8%
r 36
 
3.8%
t 36
 
3.8%
a 36
 
3.8%
i 36
 
3.8%
Other values (2) 4
 
0.4%

q40_r1_c10_3
Text

MISSING 

Distinct6
Distinct (%)100.0%
Missing994
Missing (%)99.4%
Memory size31.7 KiB
2023-12-09T22:16:25.202212image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length38
Median length24
Mean length25.16666667
Min length13

Characters and Unicode

Total characters151
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)100.0%

Sample

1st rowSpecial Exhibit Related to Curriculum
2nd rowschool merger
3rd rowFunding and credit for Arts compliance
4th rowPending funding
5th rowfree/ organized by PTA
ValueCountFrequency (%)
funding 2
 
8.7%
grant 1
 
4.3%
and 1
 
4.3%
to 1
 
4.3%
related 1
 
4.3%
exhibit 1
 
4.3%
special 1
 
4.3%
compliance 1
 
4.3%
arts 1
 
4.3%
for 1
 
4.3%
Other values (12) 12
52.2%
2023-12-09T22:16:25.542755image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
17
 
11.3%
e 15
 
9.9%
i 11
 
7.3%
r 11
 
7.3%
n 10
 
6.6%
d 8
 
5.3%
t 8
 
5.3%
a 7
 
4.6%
c 7
 
4.6%
o 7
 
4.6%
Other values (22) 50
33.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 122
80.8%
Space Separator 17
 
11.3%
Uppercase Letter 11
 
7.3%
Other Punctuation 1
 
0.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 15
12.3%
i 11
 
9.0%
r 11
 
9.0%
n 10
 
8.2%
d 8
 
6.6%
t 8
 
6.6%
a 7
 
5.7%
c 7
 
5.7%
o 7
 
5.7%
l 6
 
4.9%
Other values (11) 32
26.2%
Uppercase Letter
ValueCountFrequency (%)
P 2
18.2%
A 2
18.2%
F 1
9.1%
R 1
9.1%
E 1
9.1%
S 1
9.1%
G 1
9.1%
T 1
9.1%
C 1
9.1%
Space Separator
ValueCountFrequency (%)
17
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 133
88.1%
Common 18
 
11.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 15
 
11.3%
i 11
 
8.3%
r 11
 
8.3%
n 10
 
7.5%
d 8
 
6.0%
t 8
 
6.0%
a 7
 
5.3%
c 7
 
5.3%
o 7
 
5.3%
l 6
 
4.5%
Other values (20) 43
32.3%
Common
ValueCountFrequency (%)
17
94.4%
/ 1
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 151
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
17
 
11.3%
e 15
 
9.9%
i 11
 
7.3%
r 11
 
7.3%
n 10
 
6.6%
d 8
 
5.3%
t 8
 
5.3%
a 7
 
4.6%
c 7
 
4.6%
o 7
 
4.6%
Other values (22) 50
33.1%

q40_r1_c1_4
Text

MISSING 

Distinct110
Distinct (%)64.0%
Missing828
Missing (%)82.8%
Memory size38.7 KiB
2023-12-09T22:16:25.878765image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length59
Median length38
Mean length18.66860465
Min length4

Characters and Unicode

Total characters3211
Distinct characters66
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique89 ?
Unique (%)51.7%

Sample

1st rowTheatre for a New Audience
2nd rowSociety of the Educational Arts
3rd rowDoing Art Together
4th rowOTHER
5th rowPark Avenue Armory
ValueCountFrequency (%)
other 31
 
6.1%
arts 23
 
4.5%
of 20
 
3.9%
museum 17
 
3.3%
center 14
 
2.7%
new 11
 
2.1%
in 10
 
2.0%
for 10
 
2.0%
the 10
 
2.0%
york 9
 
1.8%
Other values (195) 357
69.7%
2023-12-09T22:16:26.391127image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
340
 
10.6%
e 283
 
8.8%
r 232
 
7.2%
t 189
 
5.9%
o 188
 
5.9%
n 173
 
5.4%
a 161
 
5.0%
i 158
 
4.9%
u 118
 
3.7%
s 114
 
3.6%
Other values (56) 1255
39.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2228
69.4%
Uppercase Letter 603
 
18.8%
Space Separator 340
 
10.6%
Other Punctuation 18
 
0.6%
Decimal Number 13
 
0.4%
Close Punctuation 4
 
0.1%
Open Punctuation 4
 
0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 283
12.7%
r 232
10.4%
t 189
 
8.5%
o 188
 
8.4%
n 173
 
7.8%
a 161
 
7.2%
i 158
 
7.1%
u 118
 
5.3%
s 114
 
5.1%
l 104
 
4.7%
Other values (16) 508
22.8%
Uppercase Letter
ValueCountFrequency (%)
A 62
10.3%
T 58
9.6%
S 55
9.1%
C 52
 
8.6%
E 51
 
8.5%
H 46
 
7.6%
M 45
 
7.5%
O 41
 
6.8%
R 35
 
5.8%
P 26
 
4.3%
Other values (15) 132
21.9%
Decimal Number
ValueCountFrequency (%)
2 4
30.8%
1 3
23.1%
9 2
15.4%
6 2
15.4%
4 1
 
7.7%
0 1
 
7.7%
Other Punctuation
ValueCountFrequency (%)
' 5
27.8%
& 5
27.8%
/ 3
16.7%
. 3
16.7%
, 2
 
11.1%
Space Separator
ValueCountFrequency (%)
340
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2831
88.2%
Common 380
 
11.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 283
 
10.0%
r 232
 
8.2%
t 189
 
6.7%
o 188
 
6.6%
n 173
 
6.1%
a 161
 
5.7%
i 158
 
5.6%
u 118
 
4.2%
s 114
 
4.0%
l 104
 
3.7%
Other values (41) 1111
39.2%
Common
ValueCountFrequency (%)
340
89.5%
' 5
 
1.3%
& 5
 
1.3%
) 4
 
1.1%
2 4
 
1.1%
( 4
 
1.1%
/ 3
 
0.8%
. 3
 
0.8%
1 3
 
0.8%
9 2
 
0.5%
Other values (5) 7
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3211
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
340
 
10.6%
e 283
 
8.8%
r 232
 
7.2%
t 189
 
5.9%
o 188
 
5.9%
n 173
 
5.4%
a 161
 
5.0%
i 158
 
4.9%
u 118
 
3.7%
s 114
 
3.6%
Other values (56) 1255
39.1%

q40_r1_c2_4
Text

MISSING 

Distinct30
Distinct (%)96.8%
Missing969
Missing (%)96.9%
Memory size32.8 KiB
2023-12-09T22:16:26.725035image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length41
Median length29
Mean length21.48387097
Min length4

Characters and Unicode

Total characters666
Distinct characters55
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29 ?
Unique (%)93.5%

Sample

1st rowMAPS
2nd rowThe Leadership Program
3rd rowThe Leadership Program
4th rowVado Diomande
5th rowPrivate Organization/Virtual Zumba
ValueCountFrequency (%)
the 4
 
4.3%
program 3
 
3.2%
leadership 3
 
3.2%
of 2
 
2.1%
with 2
 
2.1%
tlp 2
 
2.1%
university 2
 
2.1%
national 1
 
1.1%
steam 1
 
1.1%
jam 1
 
1.1%
Other values (73) 73
77.7%
2023-12-09T22:16:27.223333image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
65
 
9.8%
e 50
 
7.5%
a 50
 
7.5%
i 45
 
6.8%
n 42
 
6.3%
o 38
 
5.7%
r 38
 
5.7%
t 37
 
5.6%
s 21
 
3.2%
u 20
 
3.0%
Other values (45) 260
39.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 480
72.1%
Uppercase Letter 111
 
16.7%
Space Separator 65
 
9.8%
Dash Punctuation 4
 
0.6%
Other Punctuation 4
 
0.6%
Open Punctuation 1
 
0.2%
Close Punctuation 1
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 50
10.4%
a 50
10.4%
i 45
 
9.4%
n 42
 
8.8%
o 38
 
7.9%
r 38
 
7.9%
t 37
 
7.7%
s 21
 
4.4%
u 20
 
4.2%
d 20
 
4.2%
Other values (14) 119
24.8%
Uppercase Letter
ValueCountFrequency (%)
M 10
 
9.0%
T 10
 
9.0%
P 10
 
9.0%
L 9
 
8.1%
D 8
 
7.2%
S 6
 
5.4%
C 6
 
5.4%
E 5
 
4.5%
R 4
 
3.6%
G 4
 
3.6%
Other values (14) 39
35.1%
Other Punctuation
ValueCountFrequency (%)
/ 2
50.0%
. 1
25.0%
' 1
25.0%
Space Separator
ValueCountFrequency (%)
65
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 591
88.7%
Common 75
 
11.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 50
 
8.5%
a 50
 
8.5%
i 45
 
7.6%
n 42
 
7.1%
o 38
 
6.4%
r 38
 
6.4%
t 37
 
6.3%
s 21
 
3.6%
u 20
 
3.4%
d 20
 
3.4%
Other values (38) 230
38.9%
Common
ValueCountFrequency (%)
65
86.7%
- 4
 
5.3%
/ 2
 
2.7%
( 1
 
1.3%
) 1
 
1.3%
. 1
 
1.3%
' 1
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 666
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
65
 
9.8%
e 50
 
7.5%
a 50
 
7.5%
i 45
 
6.8%
n 42
 
6.3%
o 38
 
5.7%
r 38
 
5.7%
t 37
 
5.6%
s 21
 
3.2%
u 20
 
3.0%
Other values (45) 260
39.0%

q40_r1_c3_4
Text

MISSING 

Distinct6
Distinct (%)3.6%
Missing831
Missing (%)83.1%
Memory size36.7 KiB
2023-12-09T22:16:27.414221image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length11
Median length10
Mean length7.337278107
Min length5

Characters and Unicode

Total characters1240
Distinct characters22
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowTheater
2nd rowDance
3rd rowVisual Arts
4th rowVisual Arts
5th rowDance
ValueCountFrequency (%)
visual 50
22.8%
arts 50
22.8%
music 38
17.4%
theater 30
13.7%
dance 26
11.9%
other 18
 
8.2%
film/media 7
 
3.2%
2023-12-09T22:16:27.720548image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 138
11.1%
a 113
 
9.1%
e 111
 
9.0%
i 102
 
8.2%
t 98
 
7.9%
r 98
 
7.9%
u 88
 
7.1%
c 64
 
5.2%
l 57
 
4.6%
V 50
 
4.0%
Other values (12) 321
25.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 957
77.2%
Uppercase Letter 226
 
18.2%
Space Separator 50
 
4.0%
Other Punctuation 7
 
0.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 138
14.4%
a 113
11.8%
e 111
11.6%
i 102
10.7%
t 98
10.2%
r 98
10.2%
u 88
9.2%
c 64
6.7%
l 57
6.0%
h 48
 
5.0%
Other values (3) 40
 
4.2%
Uppercase Letter
ValueCountFrequency (%)
V 50
22.1%
A 50
22.1%
M 45
19.9%
T 30
13.3%
D 26
11.5%
O 18
 
8.0%
F 7
 
3.1%
Space Separator
ValueCountFrequency (%)
50
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1183
95.4%
Common 57
 
4.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
s 138
11.7%
a 113
9.6%
e 111
9.4%
i 102
 
8.6%
t 98
 
8.3%
r 98
 
8.3%
u 88
 
7.4%
c 64
 
5.4%
l 57
 
4.8%
V 50
 
4.2%
Other values (10) 264
22.3%
Common
ValueCountFrequency (%)
50
87.7%
/ 7
 
12.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1240
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
s 138
11.1%
a 113
 
9.1%
e 111
 
9.0%
i 102
 
8.2%
t 98
 
7.9%
r 98
 
7.9%
u 88
 
7.1%
c 64
 
5.2%
l 57
 
4.6%
V 50
 
4.0%
Other values (12) 321
25.9%

q40_r1_c4_4
Text

MISSING 

Distinct4
Distinct (%)2.4%
Missing832
Missing (%)83.2%
Memory size41.2 KiB
2023-12-09T22:16:27.934637image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length42
Median length42
Mean length34.86309524
Min length24

Characters and Unicode

Total characters5857
Distinct characters32
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowResidency (direct instruction to students)
2nd rowResidency (direct instruction to students)
3rd rowResidency (direct instruction to students)
4th rowResidency (direct instruction to students)
5th rowResidency (direct instruction to students)
ValueCountFrequency (%)
residency 90
12.6%
direct 90
12.6%
instruction 90
12.6%
to 90
12.6%
students 90
12.6%
arts 33
 
4.6%
related 33
 
4.6%
field 33
 
4.6%
trips 33
 
4.6%
in-school 31
 
4.3%
Other values (5) 104
14.5%
2023-12-09T22:16:28.286105image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 682
11.6%
e 574
9.8%
549
9.4%
s 547
9.3%
n 450
 
7.7%
i 440
 
7.5%
d 367
 
6.3%
o 346
 
5.9%
c 315
 
5.4%
r 305
 
5.2%
Other values (22) 1282
21.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4740
80.9%
Space Separator 549
 
9.4%
Uppercase Letter 357
 
6.1%
Open Punctuation 90
 
1.5%
Close Punctuation 90
 
1.5%
Dash Punctuation 31
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 682
14.4%
e 574
12.1%
s 547
11.5%
n 450
9.5%
i 440
9.3%
d 367
7.7%
o 346
7.3%
c 315
6.6%
r 305
6.4%
u 211
 
4.5%
Other values (9) 503
10.6%
Uppercase Letter
ValueCountFrequency (%)
R 123
34.5%
T 47
 
13.2%
A 33
 
9.2%
F 33
 
9.2%
W 31
 
8.7%
S 31
 
8.7%
I 31
 
8.7%
P 14
 
3.9%
D 14
 
3.9%
Space Separator
ValueCountFrequency (%)
549
100.0%
Open Punctuation
ValueCountFrequency (%)
( 90
100.0%
Close Punctuation
ValueCountFrequency (%)
) 90
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 31
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 5097
87.0%
Common 760
 
13.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 682
13.4%
e 574
11.3%
s 547
10.7%
n 450
8.8%
i 440
8.6%
d 367
7.2%
o 346
6.8%
c 315
 
6.2%
r 305
 
6.0%
u 211
 
4.1%
Other values (18) 860
16.9%
Common
ValueCountFrequency (%)
549
72.2%
( 90
 
11.8%
) 90
 
11.8%
- 31
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5857
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 682
11.6%
e 574
9.8%
549
9.4%
s 547
9.3%
n 450
 
7.7%
i 440
 
7.5%
d 367
 
6.3%
o 346
 
5.9%
c 315
 
5.4%
r 305
 
5.2%
Other values (22) 1282
21.9%

q40_r1_c5_4
Text

MISSING 

Distinct4
Distinct (%)2.4%
Missing832
Missing (%)83.2%
Memory size35.6 KiB
2023-12-09T22:16:28.404533image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters168
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.6%

Sample

1st row5
2nd row5
3rd row5
4th row5
5th row5
ValueCountFrequency (%)
5 148
88.1%
4 17
 
10.1%
3 2
 
1.2%
2 1
 
0.6%
2023-12-09T22:16:28.637975image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 148
88.1%
4 17
 
10.1%
3 2
 
1.2%
2 1
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 168
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 148
88.1%
4 17
 
10.1%
3 2
 
1.2%
2 1
 
0.6%

Most occurring scripts

ValueCountFrequency (%)
Common 168
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 148
88.1%
4 17
 
10.1%
3 2
 
1.2%
2 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 168
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 148
88.1%
4 17
 
10.1%
3 2
 
1.2%
2 1
 
0.6%

q40_r1_c6_4
Text

MISSING 

Distinct78
Distinct (%)47.9%
Missing837
Missing (%)83.7%
Memory size35.7 KiB
2023-12-09T22:16:28.927600image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length4
Median length2
Mean length2.325153374
Min length1

Characters and Unicode

Total characters379
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique51 ?
Unique (%)31.3%

Sample

1st row52
2nd row48
3rd row100
4th row92
5th row329
ValueCountFrequency (%)
100 16
 
9.8%
0 7
 
4.3%
75 7
 
4.3%
50 6
 
3.7%
80 6
 
3.7%
150 5
 
3.1%
30 5
 
3.1%
250 5
 
3.1%
25 5
 
3.1%
20 4
 
2.5%
Other values (68) 97
59.5%
2023-12-09T22:16:29.380227image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 116
30.6%
1 55
14.5%
5 52
13.7%
2 46
 
12.1%
3 29
 
7.7%
8 21
 
5.5%
4 18
 
4.7%
7 17
 
4.5%
6 13
 
3.4%
9 12
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 379
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 116
30.6%
1 55
14.5%
5 52
13.7%
2 46
 
12.1%
3 29
 
7.7%
8 21
 
5.5%
4 18
 
4.7%
7 17
 
4.5%
6 13
 
3.4%
9 12
 
3.2%

Most occurring scripts

ValueCountFrequency (%)
Common 379
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 116
30.6%
1 55
14.5%
5 52
13.7%
2 46
 
12.1%
3 29
 
7.7%
8 21
 
5.5%
4 18
 
4.7%
7 17
 
4.5%
6 13
 
3.4%
9 12
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 379
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 116
30.6%
1 55
14.5%
5 52
13.7%
2 46
 
12.1%
3 29
 
7.7%
8 21
 
5.5%
4 18
 
4.7%
7 17
 
4.5%
6 13
 
3.4%
9 12
 
3.2%

q40_r1_c7_4
Text

MISSING 

Distinct36
Distinct (%)22.0%
Missing836
Missing (%)83.6%
Memory size35.6 KiB
2023-12-09T22:16:29.599624image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2.5
Mean length1.573170732
Min length1

Characters and Unicode

Total characters258
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)11.0%

Sample

1st row20
2nd row10
3rd row50
4th row20
5th row1
ValueCountFrequency (%)
1 20
12.2%
2 18
 
11.0%
10 18
 
11.0%
20 13
 
7.9%
15 11
 
6.7%
5 9
 
5.5%
4 8
 
4.9%
25 8
 
4.9%
3 5
 
3.0%
12 5
 
3.0%
Other values (26) 49
29.9%
2023-12-09T22:16:29.945853image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 67
26.0%
0 51
19.8%
2 49
19.0%
5 38
14.7%
4 14
 
5.4%
3 14
 
5.4%
6 13
 
5.0%
8 6
 
2.3%
9 3
 
1.2%
7 3
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 258
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 67
26.0%
0 51
19.8%
2 49
19.0%
5 38
14.7%
4 14
 
5.4%
3 14
 
5.4%
6 13
 
5.0%
8 6
 
2.3%
9 3
 
1.2%
7 3
 
1.2%

Most occurring scripts

ValueCountFrequency (%)
Common 258
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 67
26.0%
0 51
19.8%
2 49
19.0%
5 38
14.7%
4 14
 
5.4%
3 14
 
5.4%
6 13
 
5.0%
8 6
 
2.3%
9 3
 
1.2%
7 3
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 258
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 67
26.0%
0 51
19.8%
2 49
19.0%
5 38
14.7%
4 14
 
5.4%
3 14
 
5.4%
6 13
 
5.0%
8 6
 
2.3%
9 3
 
1.2%
7 3
 
1.2%

q40_r1_c8_4
Text

MISSING 

Distinct3
Distinct (%)1.8%
Missing836
Missing (%)83.6%
Memory size36.0 KiB
2023-12-09T22:16:30.096274image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length9
Median length3
Mean length4.042682927
Min length2

Characters and Unicode

Total characters663
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowYes
2nd rowYes
3rd rowYes
4th rowYes
5th rowYes
ValueCountFrequency (%)
yes 132
80.5%
uncertain 29
 
17.7%
no 3
 
1.8%
2023-12-09T22:16:30.390902image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 161
24.3%
Y 132
19.9%
s 132
19.9%
n 58
 
8.7%
U 29
 
4.4%
c 29
 
4.4%
r 29
 
4.4%
t 29
 
4.4%
a 29
 
4.4%
i 29
 
4.4%
Other values (2) 6
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 499
75.3%
Uppercase Letter 164
 
24.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 161
32.3%
s 132
26.5%
n 58
 
11.6%
c 29
 
5.8%
r 29
 
5.8%
t 29
 
5.8%
a 29
 
5.8%
i 29
 
5.8%
o 3
 
0.6%
Uppercase Letter
ValueCountFrequency (%)
Y 132
80.5%
U 29
 
17.7%
N 3
 
1.8%

Most occurring scripts

ValueCountFrequency (%)
Latin 663
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 161
24.3%
Y 132
19.9%
s 132
19.9%
n 58
 
8.7%
U 29
 
4.4%
c 29
 
4.4%
r 29
 
4.4%
t 29
 
4.4%
a 29
 
4.4%
i 29
 
4.4%
Other values (2) 6
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 663
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 161
24.3%
Y 132
19.9%
s 132
19.9%
n 58
 
8.7%
U 29
 
4.4%
c 29
 
4.4%
r 29
 
4.4%
t 29
 
4.4%
a 29
 
4.4%
i 29
 
4.4%
Other values (2) 6
 
0.9%

q40_r1_c10_4
Text

MISSING 

Distinct7
Distinct (%)100.0%
Missing993
Missing (%)99.3%
Memory size31.7 KiB
2023-12-09T22:16:30.604024image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length41
Median length15
Mean length18.85714286
Min length7

Characters and Unicode

Total characters132
Distinct characters32
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)100.0%

Sample

1st rowCASA GRANT
2nd rowremote activity
3rd rowschool merger
4th rowUnit of study not scheduled for next year
5th rowDepending on Grant
ValueCountFrequency (%)
grant 2
 
9.1%
school 2
 
9.1%
depending 1
 
4.5%
casa 1
 
4.5%
funding 1
 
4.5%
program 1
 
4.5%
after 1
 
4.5%
virtual 1
 
4.5%
activity 1
 
4.5%
remote 1
 
4.5%
Other values (10) 10
45.5%
2023-12-09T22:16:30.953668image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
15
 
11.4%
e 11
 
8.3%
t 10
 
7.6%
o 10
 
7.6%
r 10
 
7.6%
n 9
 
6.8%
i 6
 
4.5%
d 5
 
3.8%
a 5
 
3.8%
f 4
 
3.0%
Other values (22) 47
35.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 101
76.5%
Uppercase Letter 16
 
12.1%
Space Separator 15
 
11.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 11
10.9%
t 10
 
9.9%
o 10
 
9.9%
r 10
 
9.9%
n 9
 
8.9%
i 6
 
5.9%
d 5
 
5.0%
a 5
 
5.0%
f 4
 
4.0%
l 4
 
4.0%
Other values (10) 27
26.7%
Uppercase Letter
ValueCountFrequency (%)
A 4
25.0%
G 2
12.5%
S 2
12.5%
N 1
 
6.2%
T 1
 
6.2%
V 1
 
6.2%
D 1
 
6.2%
R 1
 
6.2%
C 1
 
6.2%
U 1
 
6.2%
Space Separator
ValueCountFrequency (%)
15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 117
88.6%
Common 15
 
11.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 11
 
9.4%
t 10
 
8.5%
o 10
 
8.5%
r 10
 
8.5%
n 9
 
7.7%
i 6
 
5.1%
d 5
 
4.3%
a 5
 
4.3%
f 4
 
3.4%
A 4
 
3.4%
Other values (21) 43
36.8%
Common
ValueCountFrequency (%)
15
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 132
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
15
 
11.4%
e 11
 
8.3%
t 10
 
7.6%
o 10
 
7.6%
r 10
 
7.6%
n 9
 
6.8%
i 6
 
4.5%
d 5
 
3.8%
a 5
 
3.8%
f 4
 
3.0%
Other values (22) 47
35.6%

q40_r1_c1_5
Text

MISSING 

Distinct74
Distinct (%)68.5%
Missing892
Missing (%)89.2%
Memory size35.9 KiB
2023-12-09T22:16:31.325184image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length59
Median length30
Mean length17.55555556
Min length5

Characters and Unicode

Total characters1896
Distinct characters61
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique62 ?
Unique (%)57.4%

Sample

1st rowSociety of the Educational Arts
2nd rowEducation Through Music
3rd rowBroadway Bridges
4th rowAbrons Arts Center/Henry Street Settlement
5th rowNational Dance Institute
ValueCountFrequency (%)
other 22
 
7.5%
of 13
 
4.4%
arts 12
 
4.1%
museum 8
 
2.7%
music 6
 
2.0%
new 6
 
2.0%
the 6
 
2.0%
street 5
 
1.7%
york 4
 
1.4%
settlement 4
 
1.4%
Other values (142) 208
70.7%
2023-12-09T22:16:31.861803image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
186
 
9.8%
e 157
 
8.3%
t 143
 
7.5%
r 122
 
6.4%
o 120
 
6.3%
a 105
 
5.5%
n 102
 
5.4%
i 93
 
4.9%
s 75
 
4.0%
u 67
 
3.5%
Other values (51) 726
38.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1322
69.7%
Uppercase Letter 368
 
19.4%
Space Separator 186
 
9.8%
Other Punctuation 9
 
0.5%
Decimal Number 8
 
0.4%
Dash Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 157
11.9%
t 143
10.8%
r 122
9.2%
o 120
9.1%
a 105
 
7.9%
n 102
 
7.7%
i 93
 
7.0%
s 75
 
5.7%
u 67
 
5.1%
l 65
 
4.9%
Other values (15) 273
20.7%
Uppercase Letter
ValueCountFrequency (%)
T 35
 
9.5%
H 30
 
8.2%
S 29
 
7.9%
M 29
 
7.9%
E 29
 
7.9%
C 29
 
7.9%
O 28
 
7.6%
A 27
 
7.3%
R 25
 
6.8%
N 16
 
4.3%
Other values (14) 91
24.7%
Decimal Number
ValueCountFrequency (%)
2 4
50.0%
4 2
25.0%
9 1
 
12.5%
1 1
 
12.5%
Other Punctuation
ValueCountFrequency (%)
/ 3
33.3%
' 2
22.2%
. 2
22.2%
& 2
22.2%
Space Separator
ValueCountFrequency (%)
186
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1690
89.1%
Common 206
 
10.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 157
 
9.3%
t 143
 
8.5%
r 122
 
7.2%
o 120
 
7.1%
a 105
 
6.2%
n 102
 
6.0%
i 93
 
5.5%
s 75
 
4.4%
u 67
 
4.0%
l 65
 
3.8%
Other values (39) 641
37.9%
Common
ValueCountFrequency (%)
186
90.3%
2 4
 
1.9%
/ 3
 
1.5%
' 2
 
1.0%
. 2
 
1.0%
& 2
 
1.0%
4 2
 
1.0%
9 1
 
0.5%
- 1
 
0.5%
1 1
 
0.5%
Other values (2) 2
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1896
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
186
 
9.8%
e 157
 
8.3%
t 143
 
7.5%
r 122
 
6.4%
o 120
 
6.3%
a 105
 
5.5%
n 102
 
5.4%
i 93
 
4.9%
s 75
 
4.0%
u 67
 
3.5%
Other values (51) 726
38.3%

q40_r1_c2_5
Text

MISSING 

Distinct21
Distinct (%)95.5%
Missing978
Missing (%)97.8%
Memory size32.3 KiB
2023-12-09T22:16:32.150104image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length39
Median length24
Mean length19.77272727
Min length3

Characters and Unicode

Total characters435
Distinct characters46
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)90.9%

Sample

1st rowNational Portrait Gallery
2nd rowNew York Cares
3rd rowHold On to Your Music
4th rowTap in Motion
5th rowMeet the Writers
ValueCountFrequency (%)
the 5
 
6.9%
center 3
 
4.2%
of 2
 
2.8%
kennedy 2
 
2.8%
york 2
 
2.8%
new 2
 
2.8%
in 2
 
2.8%
motion 2
 
2.8%
art 2
 
2.8%
company 2
 
2.8%
Other values (47) 48
66.7%
2023-12-09T22:16:32.588197image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
50
 
11.5%
e 38
 
8.7%
n 31
 
7.1%
i 29
 
6.7%
r 28
 
6.4%
o 27
 
6.2%
t 26
 
6.0%
a 21
 
4.8%
u 15
 
3.4%
d 13
 
3.0%
Other values (36) 157
36.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 302
69.4%
Uppercase Letter 80
 
18.4%
Space Separator 50
 
11.5%
Decimal Number 1
 
0.2%
Other Punctuation 1
 
0.2%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 38
12.6%
n 31
10.3%
i 29
9.6%
r 28
9.3%
o 27
8.9%
t 26
8.6%
a 21
 
7.0%
u 15
 
5.0%
d 13
 
4.3%
s 12
 
4.0%
Other values (11) 62
20.5%
Uppercase Letter
ValueCountFrequency (%)
C 13
16.2%
M 8
10.0%
T 8
10.0%
S 8
10.0%
Y 6
 
7.5%
N 5
 
6.2%
H 5
 
6.2%
E 4
 
5.0%
P 3
 
3.8%
A 3
 
3.8%
Other values (11) 17
21.2%
Space Separator
ValueCountFrequency (%)
50
100.0%
Decimal Number
ValueCountFrequency (%)
1 1
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 382
87.8%
Common 53
 
12.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 38
 
9.9%
n 31
 
8.1%
i 29
 
7.6%
r 28
 
7.3%
o 27
 
7.1%
t 26
 
6.8%
a 21
 
5.5%
u 15
 
3.9%
d 13
 
3.4%
C 13
 
3.4%
Other values (32) 141
36.9%
Common
ValueCountFrequency (%)
50
94.3%
1 1
 
1.9%
& 1
 
1.9%
- 1
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 435
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
50
 
11.5%
e 38
 
8.7%
n 31
 
7.1%
i 29
 
6.7%
r 28
 
6.4%
o 27
 
6.2%
t 26
 
6.0%
a 21
 
4.8%
u 15
 
3.4%
d 13
 
3.0%
Other values (36) 157
36.1%

q40_r1_c3_5
Text

MISSING 

Distinct6
Distinct (%)5.6%
Missing893
Missing (%)89.3%
Memory size34.7 KiB
2023-12-09T22:16:32.786606image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length11
Median length10
Mean length7.102803738
Min length5

Characters and Unicode

Total characters760
Distinct characters22
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowMusic
2nd rowMusic
3rd rowTheater
4th rowMusic
5th rowDance
ValueCountFrequency (%)
visual 25
18.9%
arts 25
18.9%
theater 25
18.9%
music 24
18.2%
dance 20
15.2%
other 8
 
6.1%
film/media 5
 
3.8%
2023-12-09T22:16:33.117769image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 83
10.9%
a 75
 
9.9%
s 74
 
9.7%
i 59
 
7.8%
r 58
 
7.6%
t 58
 
7.6%
u 49
 
6.4%
c 44
 
5.8%
h 33
 
4.3%
l 30
 
3.9%
Other values (12) 197
25.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 593
78.0%
Uppercase Letter 137
 
18.0%
Space Separator 25
 
3.3%
Other Punctuation 5
 
0.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 83
14.0%
a 75
12.6%
s 74
12.5%
i 59
9.9%
r 58
9.8%
t 58
9.8%
u 49
8.3%
c 44
7.4%
h 33
 
5.6%
l 30
 
5.1%
Other values (3) 30
 
5.1%
Uppercase Letter
ValueCountFrequency (%)
M 29
21.2%
V 25
18.2%
T 25
18.2%
A 25
18.2%
D 20
14.6%
O 8
 
5.8%
F 5
 
3.6%
Space Separator
ValueCountFrequency (%)
25
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 730
96.1%
Common 30
 
3.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 83
11.4%
a 75
10.3%
s 74
10.1%
i 59
 
8.1%
r 58
 
7.9%
t 58
 
7.9%
u 49
 
6.7%
c 44
 
6.0%
h 33
 
4.5%
l 30
 
4.1%
Other values (10) 167
22.9%
Common
ValueCountFrequency (%)
25
83.3%
/ 5
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 760
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 83
10.9%
a 75
 
9.9%
s 74
 
9.7%
i 59
 
7.8%
r 58
 
7.6%
t 58
 
7.6%
u 49
 
6.4%
c 44
 
5.8%
h 33
 
4.3%
l 30
 
3.9%
Other values (12) 197
25.9%

q40_r1_c4_5
Text

MISSING 

Distinct4
Distinct (%)3.8%
Missing894
Missing (%)89.4%
Memory size37.4 KiB
2023-12-09T22:16:33.338973image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length42
Median length32
Mean length33.5754717
Min length24

Characters and Unicode

Total characters3559
Distinct characters32
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowResidency (direct instruction to students)
2nd rowResidency (direct instruction to students)
3rd rowArts Related Field Trips
4th rowResidency (direct instruction to students)
5th rowResidency (direct instruction to students)
ValueCountFrequency (%)
residency 51
11.3%
direct 51
11.3%
instruction 51
11.3%
to 51
11.3%
students 51
11.3%
arts 31
6.9%
related 31
6.9%
field 31
6.9%
trips 31
6.9%
in-school 19
 
4.2%
Other values (5) 53
11.8%
2023-12-09T22:16:33.692265image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 411
11.5%
e 346
9.7%
345
9.7%
s 333
9.4%
i 271
 
7.6%
n 252
 
7.1%
d 234
 
6.6%
o 193
 
5.4%
r 193
 
5.4%
c 177
 
5.0%
Other values (22) 804
22.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2846
80.0%
Space Separator 345
 
9.7%
Uppercase Letter 247
 
6.9%
Open Punctuation 51
 
1.4%
Close Punctuation 51
 
1.4%
Dash Punctuation 19
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 411
14.4%
e 346
12.2%
s 333
11.7%
i 271
9.5%
n 252
8.9%
d 234
8.2%
o 193
6.8%
r 193
6.8%
c 177
6.2%
u 121
 
4.3%
Other values (9) 315
11.1%
Uppercase Letter
ValueCountFrequency (%)
R 82
33.2%
T 36
14.6%
A 31
 
12.6%
F 31
 
12.6%
W 19
 
7.7%
S 19
 
7.7%
I 19
 
7.7%
P 5
 
2.0%
D 5
 
2.0%
Space Separator
ValueCountFrequency (%)
345
100.0%
Open Punctuation
ValueCountFrequency (%)
( 51
100.0%
Close Punctuation
ValueCountFrequency (%)
) 51
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3093
86.9%
Common 466
 
13.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 411
13.3%
e 346
11.2%
s 333
10.8%
i 271
8.8%
n 252
8.1%
d 234
7.6%
o 193
 
6.2%
r 193
 
6.2%
c 177
 
5.7%
u 121
 
3.9%
Other values (18) 562
18.2%
Common
ValueCountFrequency (%)
345
74.0%
( 51
 
10.9%
) 51
 
10.9%
- 19
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3559
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 411
11.5%
e 346
9.7%
345
9.7%
s 333
9.4%
i 271
 
7.6%
n 252
 
7.1%
d 234
 
6.6%
o 193
 
5.4%
r 193
 
5.4%
c 177
 
5.0%
Other values (22) 804
22.6%

q40_r1_c5_5
Text

MISSING 

Distinct3
Distinct (%)2.8%
Missing892
Missing (%)89.2%
Memory size34.1 KiB
2023-12-09T22:16:33.810278image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters108
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row5
2nd row5
3rd row5
4th row5
5th row5
ValueCountFrequency (%)
5 94
87.0%
4 12
 
11.1%
3 2
 
1.9%
2023-12-09T22:16:34.074661image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 94
87.0%
4 12
 
11.1%
3 2
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 108
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 94
87.0%
4 12
 
11.1%
3 2
 
1.9%

Most occurring scripts

ValueCountFrequency (%)
Common 108
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 94
87.0%
4 12
 
11.1%
3 2
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 108
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 94
87.0%
4 12
 
11.1%
3 2
 
1.9%

q40_r1_c6_5
Text

MISSING 

Distinct61
Distinct (%)58.1%
Missing895
Missing (%)89.5%
Memory size34.2 KiB
2023-12-09T22:16:34.391574image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.428571429
Min length1

Characters and Unicode

Total characters255
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique41 ?
Unique (%)39.0%

Sample

1st row48
2nd row300
3rd row15
4th row15
5th row120
ValueCountFrequency (%)
100 10
 
9.5%
300 5
 
4.8%
50 5
 
4.8%
10 5
 
4.8%
60 4
 
3.8%
400 4
 
3.8%
35 3
 
2.9%
250 3
 
2.9%
25 3
 
2.9%
200 2
 
1.9%
Other values (51) 61
58.1%
2023-12-09T22:16:34.791290image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 82
32.2%
5 32
 
12.5%
1 29
 
11.4%
2 28
 
11.0%
3 27
 
10.6%
4 18
 
7.1%
7 14
 
5.5%
6 11
 
4.3%
8 8
 
3.1%
9 6
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 255
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 82
32.2%
5 32
 
12.5%
1 29
 
11.4%
2 28
 
11.0%
3 27
 
10.6%
4 18
 
7.1%
7 14
 
5.5%
6 11
 
4.3%
8 8
 
3.1%
9 6
 
2.4%

Most occurring scripts

ValueCountFrequency (%)
Common 255
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 82
32.2%
5 32
 
12.5%
1 29
 
11.4%
2 28
 
11.0%
3 27
 
10.6%
4 18
 
7.1%
7 14
 
5.5%
6 11
 
4.3%
8 8
 
3.1%
9 6
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 255
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 82
32.2%
5 32
 
12.5%
1 29
 
11.4%
2 28
 
11.0%
3 27
 
10.6%
4 18
 
7.1%
7 14
 
5.5%
6 11
 
4.3%
8 8
 
3.1%
9 6
 
2.4%

q40_r1_c7_5
Text

MISSING 

Distinct36
Distinct (%)34.3%
Missing895
Missing (%)89.5%
Memory size34.1 KiB
2023-12-09T22:16:35.014170image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length1.580952381
Min length1

Characters and Unicode

Total characters166
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)17.1%

Sample

1st row10
2nd row200
3rd row5
4th row10
5th row25
ValueCountFrequency (%)
2 15
14.3%
1 14
13.3%
10 11
 
10.5%
30 7
 
6.7%
3 5
 
4.8%
20 5
 
4.8%
5 4
 
3.8%
8 4
 
3.8%
4 3
 
2.9%
15 3
 
2.9%
Other values (26) 34
32.4%
2023-12-09T22:16:35.379834image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 41
24.7%
0 36
21.7%
2 28
16.9%
5 17
10.2%
3 14
 
8.4%
6 10
 
6.0%
8 8
 
4.8%
4 5
 
3.0%
7 5
 
3.0%
9 2
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 166
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 41
24.7%
0 36
21.7%
2 28
16.9%
5 17
10.2%
3 14
 
8.4%
6 10
 
6.0%
8 8
 
4.8%
4 5
 
3.0%
7 5
 
3.0%
9 2
 
1.2%

Most occurring scripts

ValueCountFrequency (%)
Common 166
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 41
24.7%
0 36
21.7%
2 28
16.9%
5 17
10.2%
3 14
 
8.4%
6 10
 
6.0%
8 8
 
4.8%
4 5
 
3.0%
7 5
 
3.0%
9 2
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 166
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 41
24.7%
0 36
21.7%
2 28
16.9%
5 17
10.2%
3 14
 
8.4%
6 10
 
6.0%
8 8
 
4.8%
4 5
 
3.0%
7 5
 
3.0%
9 2
 
1.2%

q40_r1_c8_5
Text

MISSING 

Distinct3
Distinct (%)2.9%
Missing896
Missing (%)89.6%
Memory size34.3 KiB
2023-12-09T22:16:35.538704image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length9
Median length3
Mean length3.769230769
Min length2

Characters and Unicode

Total characters392
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowYes
2nd rowYes
3rd rowYes
4th rowYes
5th rowYes
ValueCountFrequency (%)
yes 86
82.7%
uncertain 14
 
13.5%
no 4
 
3.8%
2023-12-09T22:16:35.806699image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 100
25.5%
Y 86
21.9%
s 86
21.9%
n 28
 
7.1%
U 14
 
3.6%
c 14
 
3.6%
r 14
 
3.6%
t 14
 
3.6%
a 14
 
3.6%
i 14
 
3.6%
Other values (2) 8
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 288
73.5%
Uppercase Letter 104
 
26.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 100
34.7%
s 86
29.9%
n 28
 
9.7%
c 14
 
4.9%
r 14
 
4.9%
t 14
 
4.9%
a 14
 
4.9%
i 14
 
4.9%
o 4
 
1.4%
Uppercase Letter
ValueCountFrequency (%)
Y 86
82.7%
U 14
 
13.5%
N 4
 
3.8%

Most occurring scripts

ValueCountFrequency (%)
Latin 392
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 100
25.5%
Y 86
21.9%
s 86
21.9%
n 28
 
7.1%
U 14
 
3.6%
c 14
 
3.6%
r 14
 
3.6%
t 14
 
3.6%
a 14
 
3.6%
i 14
 
3.6%
Other values (2) 8
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 392
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 100
25.5%
Y 86
21.9%
s 86
21.9%
n 28
 
7.1%
U 14
 
3.6%
c 14
 
3.6%
r 14
 
3.6%
t 14
 
3.6%
a 14
 
3.6%
i 14
 
3.6%
Other values (2) 8
 
2.0%

q40_r1_c10_5
Text

MISSING 

Distinct7
Distinct (%)100.0%
Missing993
Missing (%)99.3%
Memory size31.7 KiB
2023-12-09T22:16:36.013217image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length29
Median length28
Mean length17.28571429
Min length6

Characters and Unicode

Total characters121
Distinct characters29
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)100.0%

Sample

1st rowRemote
2nd rowschool merger
3rd rowUnsure of funding availabiity
4th rowbudget
5th rowVirtual After School Program
ValueCountFrequency (%)
grant 2
 
11.1%
school 2
 
11.1%
remote 1
 
5.6%
expired 1
 
5.6%
virtual 1
 
5.6%
after 1
 
5.6%
program 1
 
5.6%
unsure 1
 
5.6%
of 1
 
5.6%
funding 1
 
5.6%
Other values (6) 6
33.3%
2023-12-09T22:16:36.357804image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 13
 
10.7%
11
 
9.1%
r 11
 
9.1%
t 9
 
7.4%
o 8
 
6.6%
a 8
 
6.6%
i 7
 
5.8%
m 6
 
5.0%
n 5
 
4.1%
l 5
 
4.1%
Other values (19) 38
31.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 103
85.1%
Space Separator 11
 
9.1%
Uppercase Letter 7
 
5.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 13
12.6%
r 11
10.7%
t 9
 
8.7%
o 8
 
7.8%
a 8
 
7.8%
i 7
 
6.8%
m 6
 
5.8%
n 5
 
4.9%
l 5
 
4.9%
g 5
 
4.9%
Other values (11) 26
25.2%
Uppercase Letter
ValueCountFrequency (%)
U 1
14.3%
R 1
14.3%
V 1
14.3%
P 1
14.3%
S 1
14.3%
A 1
14.3%
G 1
14.3%
Space Separator
ValueCountFrequency (%)
11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 110
90.9%
Common 11
 
9.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 13
 
11.8%
r 11
 
10.0%
t 9
 
8.2%
o 8
 
7.3%
a 8
 
7.3%
i 7
 
6.4%
m 6
 
5.5%
n 5
 
4.5%
l 5
 
4.5%
g 5
 
4.5%
Other values (18) 33
30.0%
Common
ValueCountFrequency (%)
11
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 121
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 13
 
10.7%
11
 
9.1%
r 11
 
9.1%
t 9
 
7.4%
o 8
 
6.6%
a 8
 
6.6%
i 7
 
5.8%
m 6
 
5.0%
n 5
 
4.1%
l 5
 
4.1%
Other values (19) 38
31.4%

q41_1
Text

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size56.8 KiB
2023-12-09T22:16:36.474480image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row1
5th row1
ValueCountFrequency (%)
1 508
50.8%
0 492
49.2%
2023-12-09T22:16:36.700513image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 508
50.8%
0 492
49.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 508
50.8%
0 492
49.2%

Most occurring scripts

ValueCountFrequency (%)
Common 1000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 508
50.8%
0 492
49.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 508
50.8%
0 492
49.2%

q41_2
Text

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size56.8 KiB
2023-12-09T22:16:36.809298image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row0
3rd row0
4th row1
5th row1
ValueCountFrequency (%)
1 673
67.3%
0 327
32.7%
2023-12-09T22:16:37.036304image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 673
67.3%
0 327
32.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 673
67.3%
0 327
32.7%

Most occurring scripts

ValueCountFrequency (%)
Common 1000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 673
67.3%
0 327
32.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 673
67.3%
0 327
32.7%

q41_3
Text

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size56.8 KiB
2023-12-09T22:16:37.151073image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row0
4th row1
5th row1
ValueCountFrequency (%)
1 766
76.6%
0 234
 
23.4%
2023-12-09T22:16:37.403709image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 766
76.6%
0 234
 
23.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 766
76.6%
0 234
 
23.4%

Most occurring scripts

ValueCountFrequency (%)
Common 1000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 766
76.6%
0 234
 
23.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 766
76.6%
0 234
 
23.4%

q41_4
Text

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size56.8 KiB
2023-12-09T22:16:37.518420image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row1
ValueCountFrequency (%)
1 588
58.8%
0 412
41.2%
2023-12-09T22:16:37.751182image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 588
58.8%
0 412
41.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 588
58.8%
0 412
41.2%

Most occurring scripts

ValueCountFrequency (%)
Common 1000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 588
58.8%
0 412
41.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 588
58.8%
0 412
41.2%

q41_5
Text

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size56.8 KiB
2023-12-09T22:16:37.863490image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 666
66.6%
1 334
33.4%
2023-12-09T22:16:38.098034image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 666
66.6%
1 334
33.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 666
66.6%
1 334
33.4%

Most occurring scripts

ValueCountFrequency (%)
Common 1000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 666
66.6%
1 334
33.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 666
66.6%
1 334
33.4%

q41_6
Text

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size56.8 KiB
2023-12-09T22:16:38.215772image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row1
5th row0
ValueCountFrequency (%)
1 519
51.9%
0 481
48.1%
2023-12-09T22:16:38.455152image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 519
51.9%
0 481
48.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 519
51.9%
0 481
48.1%

Most occurring scripts

ValueCountFrequency (%)
Common 1000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 519
51.9%
0 481
48.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 519
51.9%
0 481
48.1%

q41_7
Text

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size56.8 KiB
2023-12-09T22:16:38.566726image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row0
3rd row0
4th row1
5th row1
ValueCountFrequency (%)
1 649
64.9%
0 351
35.1%
2023-12-09T22:16:38.798677image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 649
64.9%
0 351
35.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 649
64.9%
0 351
35.1%

Most occurring scripts

ValueCountFrequency (%)
Common 1000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 649
64.9%
0 351
35.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 649
64.9%
0 351
35.1%

q41_8
Text

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size56.8 KiB
2023-12-09T22:16:38.912180image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row0
3rd row0
4th row1
5th row1
ValueCountFrequency (%)
1 783
78.3%
0 217
 
21.7%
2023-12-09T22:16:39.149391image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 783
78.3%
0 217
 
21.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 783
78.3%
0 217
 
21.7%

Most occurring scripts

ValueCountFrequency (%)
Common 1000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 783
78.3%
0 217
 
21.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 783
78.3%
0 217
 
21.7%

q41_9
Text

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size56.8 KiB
2023-12-09T22:16:39.265534image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 619
61.9%
1 381
38.1%
2023-12-09T22:16:39.503263image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 619
61.9%
1 381
38.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 619
61.9%
1 381
38.1%

Most occurring scripts

ValueCountFrequency (%)
Common 1000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 619
61.9%
1 381
38.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 619
61.9%
1 381
38.1%

q41_10
Text

Distinct45
Distinct (%)4.5%
Missing3
Missing (%)0.3%
Memory size58.4 KiB
2023-12-09T22:16:39.839086image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length165
Median length1
Mean length2.720160481
Min length1

Characters and Unicode

Total characters2712
Distinct characters60
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique43 ?
Unique (%)4.3%

Sample

1st row0
2nd row0
3rd rowDue to the pandemic we had lack of arts providers
4th row0
5th rowGoogle Classroom feedback, Flipgrid
ValueCountFrequency (%)
0 952
78.7%
and 10
 
0.8%
arts 9
 
0.7%
google 7
 
0.6%
student 7
 
0.6%
padlet 5
 
0.4%
in 5
 
0.4%
the 5
 
0.4%
of 5
 
0.4%
this 4
 
0.3%
Other values (144) 200
 
16.5%
2023-12-09T22:16:40.351445image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 952
35.1%
212
 
7.8%
e 162
 
6.0%
s 137
 
5.1%
t 123
 
4.5%
a 108
 
4.0%
o 106
 
3.9%
i 102
 
3.8%
r 98
 
3.6%
n 95
 
3.5%
Other values (50) 617
22.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1370
50.5%
Decimal Number 954
35.2%
Space Separator 212
 
7.8%
Uppercase Letter 134
 
4.9%
Other Punctuation 36
 
1.3%
Dash Punctuation 2
 
0.1%
Open Punctuation 2
 
0.1%
Close Punctuation 2
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 162
11.8%
s 137
10.0%
t 123
9.0%
a 108
 
7.9%
o 106
 
7.7%
i 102
 
7.4%
r 98
 
7.2%
n 95
 
6.9%
d 70
 
5.1%
l 65
 
4.7%
Other values (16) 304
22.2%
Uppercase Letter
ValueCountFrequency (%)
S 18
13.4%
C 13
 
9.7%
A 12
 
9.0%
P 11
 
8.2%
E 10
 
7.5%
T 8
 
6.0%
V 7
 
5.2%
G 7
 
5.2%
N 7
 
5.2%
D 6
 
4.5%
Other values (13) 35
26.1%
Other Punctuation
ValueCountFrequency (%)
, 24
66.7%
. 9
 
25.0%
/ 2
 
5.6%
; 1
 
2.8%
Decimal Number
ValueCountFrequency (%)
0 952
99.8%
2 1
 
0.1%
9 1
 
0.1%
Space Separator
ValueCountFrequency (%)
212
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1504
55.5%
Common 1208
44.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 162
 
10.8%
s 137
 
9.1%
t 123
 
8.2%
a 108
 
7.2%
o 106
 
7.0%
i 102
 
6.8%
r 98
 
6.5%
n 95
 
6.3%
d 70
 
4.7%
l 65
 
4.3%
Other values (39) 438
29.1%
Common
ValueCountFrequency (%)
0 952
78.8%
212
 
17.5%
, 24
 
2.0%
. 9
 
0.7%
- 2
 
0.2%
/ 2
 
0.2%
( 2
 
0.2%
) 2
 
0.2%
; 1
 
0.1%
2 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2712
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 952
35.1%
212
 
7.8%
e 162
 
6.0%
s 137
 
5.1%
t 123
 
4.5%
a 108
 
4.0%
o 106
 
3.9%
i 102
 
3.8%
r 98
 
3.6%
n 95
 
3.5%
Other values (50) 617
22.8%

q42_1_rev
Text

MISSING 

Distinct913
Distinct (%)100.0%
Missing87
Missing (%)8.7%
Memory size975.6 KiB
2023-12-09T22:16:40.785289image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1762
Median length1074
Mean length859.8630887
Min length63

Characters and Unicode

Total characters785055
Distinct characters88
Distinct categories13 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique913 ?
Unique (%)100.0%

Sample

1st rowWe value the arts as essential learning experiences for our students. Although we could not host live events this year, we worked with arts organizations to bring in virtual experiences, and we incorporated art in our classrooms for both virtual and in-person students. Our arts partners, Third Street Music School Setttlement, Mark DeGarmo Dance, and Arts for All, developed live virtual curriculum which both in-person and remote students participated in together. This fostered a feeling of classroom community as well as creative learning. Our in-house STEAM program offered many opportunities for creative exploration, and we organized materials for all of our remote students so that they could create mobiles, sculptures, collages, and drawings at home. In Technology Arts, our students continued to explore expression and the design process through coding, animation, robotics, and a variety of hands-on media. One of our students created an animation that was included in the Manhattan Borough Arts Festival, and many of our students contributed artworks to the D01 Arts Showcase. We also highlighted the arts in our Career Day event. Our presenters included a film and theatre director, a comedy writer, a woodworker, and an actor. We continually seek to share with students our conviction that the arts are central to understanding ourselves and the world.
2nd rowWe strongly believe that the arts should be an important part of a school's academic program. We have participated in and developed a wide variety of educational programs and activities to support the inclusion of the arts (music, visual arts, dance and theater) in daily curriculum offerings to our students. Many community agencies support us, including Third Street Music School Settlement and Studio in a School. Visitors to PS 19 often comment on the extent to which the students are engaged with their work. We are particularly proud of our school's warm and sociable atmosphere and productive learning environment.
3rd rowDue to the pandemic, we did not have the arts programs we would normally have at PS20M. Going forward we would like to continue to provide arts programs for our students, including dance, music and theater for all ages across the school. We have worked with Ajna Dance Company, Third Street Music School Settlement, National Dance Institute (NDI) and Rosie's Theatre Kids and others to ensure we provide arts programs for our students from ages Pre-K to 5. Through these programs, our students are able to learn through the arts in addition to expressing themselves through the arts.
4th rowStudents were provided arts instruction in is visual arts and theater by certified on-site teachers. A partnership developed with a community-based organization to provide dance instruction for middle school students.
5th rowAt Public School 63, our commitment to the arts is always growing. Since the 2010-2011 school year, full-time music and visual arts instruction by certified arts teachers has been offered to all grades. In visual arts classes, students explore a variety of two and three dimensional media and techniques. Additionally, they are exposed to a wide variety of artists both contemporary and throughout history as well as careers in the arts. Usually in music, all kindergarten through second grade students are given instruction in keyboard, reading music and vocals. As students move into the upper grades, they learn additional instruments, such as the recorder, violin, trumpet, and bucket drums. To enhance our arts program, we continue our theater partnership with Scripts to Stage, Young Storytellers in 5th grade. In the 2020-21 school year due to pandemic conditions, all music instruction was provided remotely and asynchronously. Visual arts instruction was provided as push-in for hybrid students and remotely and asynchronously for fully remote learners. Scripts to Stage was also provided remotely.
ValueCountFrequency (%)
and 6205
 
5.1%
the 5492
 
4.5%
to 4105
 
3.4%
arts 3772
 
3.1%
in 3180
 
2.6%
students 2955
 
2.4%
of 2727
 
2.2%
our 2645
 
2.2%
a 2267
 
1.9%
we 1535
 
1.3%
Other values (6844) 86541
71.3%
2023-12-09T22:16:41.406246image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
121190
15.4%
e 68867
 
8.8%
t 58227
 
7.4%
a 52785
 
6.7%
r 49320
 
6.3%
n 45934
 
5.9%
i 45733
 
5.8%
o 45634
 
5.8%
s 45602
 
5.8%
d 26657
 
3.4%
Other values (78) 225106
28.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 623164
79.4%
Space Separator 121192
 
15.4%
Uppercase Letter 19683
 
2.5%
Other Punctuation 14361
 
1.8%
Decimal Number 3808
 
0.5%
Dash Punctuation 1717
 
0.2%
Close Punctuation 346
 
< 0.1%
Open Punctuation 341
 
< 0.1%
Control 240
 
< 0.1%
Final Punctuation 176
 
< 0.1%
Other values (3) 27
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 68867
11.1%
t 58227
 
9.3%
a 52785
 
8.5%
r 49320
 
7.9%
n 45934
 
7.4%
i 45733
 
7.3%
o 45634
 
7.3%
s 45602
 
7.3%
d 26657
 
4.3%
l 26102
 
4.2%
Other values (17) 158303
25.4%
Uppercase Letter
ValueCountFrequency (%)
S 2746
14.0%
A 2265
11.5%
T 2083
 
10.6%
C 1348
 
6.8%
P 1232
 
6.3%
W 1082
 
5.5%
M 978
 
5.0%
O 949
 
4.8%
D 823
 
4.2%
I 819
 
4.2%
Other values (16) 5358
27.2%
Other Punctuation
ValueCountFrequency (%)
, 6764
47.1%
. 6593
45.9%
' 327
 
2.3%
/ 219
 
1.5%
: 130
 
0.9%
" 127
 
0.9%
; 84
 
0.6%
& 51
 
0.4%
! 37
 
0.3%
% 15
 
0.1%
Other values (2) 14
 
0.1%
Decimal Number
ValueCountFrequency (%)
2 1020
26.8%
1 700
18.4%
0 569
14.9%
5 302
 
7.9%
3 274
 
7.2%
9 238
 
6.2%
8 204
 
5.4%
6 186
 
4.9%
4 178
 
4.7%
7 137
 
3.6%
Space Separator
ValueCountFrequency (%)
121190
> 99.9%
  2
 
< 0.1%
Final Punctuation
ValueCountFrequency (%)
159
90.3%
17
 
9.7%
Initial Punctuation
ValueCountFrequency (%)
17
81.0%
4
 
19.0%
Math Symbol
ValueCountFrequency (%)
+ 3
75.0%
> 1
 
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 1717
100.0%
Close Punctuation
ValueCountFrequency (%)
) 346
100.0%
Open Punctuation
ValueCountFrequency (%)
( 341
100.0%
Control
ValueCountFrequency (%)
240
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 642847
81.9%
Common 142208
 
18.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 68867
 
10.7%
t 58227
 
9.1%
a 52785
 
8.2%
r 49320
 
7.7%
n 45934
 
7.1%
i 45733
 
7.1%
o 45634
 
7.1%
s 45602
 
7.1%
d 26657
 
4.1%
l 26102
 
4.1%
Other values (43) 177986
27.7%
Common
ValueCountFrequency (%)
121190
85.2%
, 6764
 
4.8%
. 6593
 
4.6%
- 1717
 
1.2%
2 1020
 
0.7%
1 700
 
0.5%
0 569
 
0.4%
) 346
 
0.2%
( 341
 
0.2%
' 327
 
0.2%
Other values (25) 2641
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 784842
> 99.9%
Punctuation 209
 
< 0.1%
None 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
121190
15.4%
e 68867
 
8.8%
t 58227
 
7.4%
a 52785
 
6.7%
r 49320
 
6.3%
n 45934
 
5.9%
i 45733
 
5.8%
o 45634
 
5.8%
s 45602
 
5.8%
d 26657
 
3.4%
Other values (71) 224893
28.7%
Punctuation
ValueCountFrequency (%)
159
76.1%
17
 
8.1%
17
 
8.1%
12
 
5.7%
4
 
1.9%
None
ValueCountFrequency (%)
  2
50.0%
ñ 2
50.0%

q43_1
Text

MISSING 

Distinct177
Distinct (%)100.0%
Missing823
Missing (%)82.3%
Memory size135.3 KiB
2023-12-09T22:16:41.782231image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1500
Median length398
Mean length481.3615819
Min length1

Characters and Unicode

Total characters85201
Distinct characters84
Distinct categories12 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique177 ?
Unique (%)100.0%

Sample

1st rowThe pandemic had significant impact on our community. We were able to provide more Arts programming than in years past, and we are continuing to expand programming options in the upcoming school year.
2nd rowWe are a Title I dual language elementary and middle school with over 60% of students with free lunches and over 15% of students with special needs. Our school, in general, has several languages, dialects, ages and needs from all walks of life.
3rd rowIt's been a very challenging year however we are grateful we were able to incorporate our arts programming back into our school year.
4th rowDuring Covid we taught a lot of the year on ZOOM. SOme teachers did cultural zoom experiences with art organizations but it was not as many due to Covid.
5th rowDue to the Covid-19 pandemic, distancing restrictions made it necessary for our school to use the dedicated art room as a classroom and the arts teachers pushed into regular classrooms. It is our school's intent to re-dedicate the art room to its use for art only once restrictions are lifted. In addition, though we were unable to take students on field trips and to arts events outside of the classroom, students were able to attend and participate in many events and trips virtually.
ValueCountFrequency (%)
the 589
 
4.3%
to 555
 
4.1%
and 550
 
4.0%
our 358
 
2.6%
of 341
 
2.5%
in 297
 
2.2%
we 280
 
2.0%
arts 278
 
2.0%
a 276
 
2.0%
students 247
 
1.8%
Other values (2410) 9925
72.5%
2023-12-09T22:16:42.373110image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
13621
16.0%
e 7953
 
9.3%
t 5982
 
7.0%
a 5570
 
6.5%
o 5193
 
6.1%
r 5092
 
6.0%
s 4790
 
5.6%
n 4772
 
5.6%
i 4598
 
5.4%
l 3011
 
3.5%
Other values (74) 24619
28.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 67124
78.8%
Space Separator 13621
 
16.0%
Uppercase Letter 1991
 
2.3%
Other Punctuation 1482
 
1.7%
Decimal Number 572
 
0.7%
Dash Punctuation 234
 
0.3%
Control 82
 
0.1%
Open Punctuation 34
 
< 0.1%
Close Punctuation 34
 
< 0.1%
Final Punctuation 21
 
< 0.1%
Other values (2) 6
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 7953
11.8%
t 5982
 
8.9%
a 5570
 
8.3%
o 5193
 
7.7%
r 5092
 
7.6%
s 4790
 
7.1%
n 4772
 
7.1%
i 4598
 
6.9%
l 3011
 
4.5%
h 2745
 
4.1%
Other values (16) 17418
25.9%
Uppercase Letter
ValueCountFrequency (%)
T 227
11.4%
A 224
11.3%
S 201
 
10.1%
W 164
 
8.2%
O 129
 
6.5%
D 124
 
6.2%
C 123
 
6.2%
I 103
 
5.2%
P 99
 
5.0%
E 91
 
4.6%
Other values (16) 506
25.4%
Other Punctuation
ValueCountFrequency (%)
. 716
48.3%
, 625
42.2%
/ 36
 
2.4%
% 32
 
2.2%
' 26
 
1.8%
" 16
 
1.1%
: 13
 
0.9%
; 10
 
0.7%
& 6
 
0.4%
! 2
 
0.1%
Decimal Number
ValueCountFrequency (%)
2 151
26.4%
1 126
22.0%
0 115
20.1%
9 43
 
7.5%
3 37
 
6.5%
6 28
 
4.9%
5 24
 
4.2%
8 18
 
3.1%
7 17
 
3.0%
4 13
 
2.3%
Dash Punctuation
ValueCountFrequency (%)
- 230
98.3%
2
 
0.9%
2
 
0.9%
Final Punctuation
ValueCountFrequency (%)
18
85.7%
3
 
14.3%
Initial Punctuation
ValueCountFrequency (%)
3
60.0%
2
40.0%
Space Separator
ValueCountFrequency (%)
13621
100.0%
Control
ValueCountFrequency (%)
82
100.0%
Open Punctuation
ValueCountFrequency (%)
( 34
100.0%
Close Punctuation
ValueCountFrequency (%)
) 34
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 69115
81.1%
Common 16086
 
18.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 7953
11.5%
t 5982
 
8.7%
a 5570
 
8.1%
o 5193
 
7.5%
r 5092
 
7.4%
s 4790
 
6.9%
n 4772
 
6.9%
i 4598
 
6.7%
l 3011
 
4.4%
h 2745
 
4.0%
Other values (42) 19409
28.1%
Common
ValueCountFrequency (%)
13621
84.7%
. 716
 
4.5%
, 625
 
3.9%
- 230
 
1.4%
2 151
 
0.9%
1 126
 
0.8%
0 115
 
0.7%
82
 
0.5%
9 43
 
0.3%
3 37
 
0.2%
Other values (22) 340
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 85171
> 99.9%
Punctuation 30
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
13621
16.0%
e 7953
 
9.3%
t 5982
 
7.0%
a 5570
 
6.5%
o 5193
 
6.1%
r 5092
 
6.0%
s 4790
 
5.6%
n 4772
 
5.6%
i 4598
 
5.4%
l 3011
 
3.5%
Other values (68) 24589
28.9%
Punctuation
ValueCountFrequency (%)
18
60.0%
3
 
10.0%
3
 
10.0%
2
 
6.7%
2
 
6.7%
2
 
6.7%

q44_1
Text

Distinct994
Distinct (%)99.8%
Missing4
Missing (%)0.4%
Memory size69.5 KiB
2023-12-09T22:16:42.828458image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length30
Median length25
Mean length14.12751004
Min length4

Characters and Unicode

Total characters14071
Distinct characters57
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique993 ?
Unique (%)99.7%

Sample

1st rowLaura Salmon
2nd rowJacqueline Dugan
3rd rowRonnie Filippatos
4th rowBryan Glover
5th rowJenny Gouker
ValueCountFrequency (%)
michael 14
 
0.7%
maria 11
 
0.5%
elizabeth 11
 
0.5%
a 11
 
0.5%
jennifer 10
 
0.5%
nicole 10
 
0.5%
laura 9
 
0.4%
karen 8
 
0.4%
james 8
 
0.4%
lisa 8
 
0.4%
Other values (1488) 1958
95.1%
2023-12-09T22:16:43.450552image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 1484
 
10.5%
e 1302
 
9.3%
1066
 
7.6%
n 1046
 
7.4%
i 978
 
7.0%
r 888
 
6.3%
o 776
 
5.5%
l 726
 
5.2%
s 523
 
3.7%
t 444
 
3.2%
Other values (47) 4838
34.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 10612
75.4%
Uppercase Letter 2312
 
16.4%
Space Separator 1066
 
7.6%
Dash Punctuation 47
 
0.3%
Other Punctuation 34
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 1484
14.0%
e 1302
12.3%
n 1046
9.9%
i 978
9.2%
r 888
8.4%
o 776
 
7.3%
l 726
 
6.8%
s 523
 
4.9%
t 444
 
4.2%
h 343
 
3.2%
Other values (17) 2102
19.8%
Uppercase Letter
ValueCountFrequency (%)
M 230
 
9.9%
S 202
 
8.7%
A 188
 
8.1%
C 159
 
6.9%
J 144
 
6.2%
L 140
 
6.1%
D 132
 
5.7%
R 131
 
5.7%
B 115
 
5.0%
K 107
 
4.6%
Other values (15) 764
33.0%
Other Punctuation
ValueCountFrequency (%)
. 27
79.4%
' 6
 
17.6%
/ 1
 
2.9%
Space Separator
ValueCountFrequency (%)
1066
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 47
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 12924
91.8%
Common 1147
 
8.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 1484
 
11.5%
e 1302
 
10.1%
n 1046
 
8.1%
i 978
 
7.6%
r 888
 
6.9%
o 776
 
6.0%
l 726
 
5.6%
s 523
 
4.0%
t 444
 
3.4%
h 343
 
2.7%
Other values (42) 4414
34.2%
Common
ValueCountFrequency (%)
1066
92.9%
- 47
 
4.1%
. 27
 
2.4%
' 6
 
0.5%
/ 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14070
> 99.9%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 1484
 
10.5%
e 1302
 
9.3%
1066
 
7.6%
n 1046
 
7.4%
i 978
 
7.0%
r 888
 
6.3%
o 776
 
5.5%
l 726
 
5.2%
s 523
 
3.7%
t 444
 
3.2%
Other values (46) 4837
34.4%
None
ValueCountFrequency (%)
é 1
100.0%

q44_2
Text

MISSING 

Distinct218
Distinct (%)22.2%
Missing18
Missing (%)1.8%
Memory size69.8 KiB
2023-12-09T22:16:43.693251image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length54
Median length47
Mean length15.05295316
Min length2

Characters and Unicode

Total characters14782
Distinct characters56
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique162 ?
Unique (%)16.5%

Sample

1st rowAssistant Principal
2nd rowPrincipal
3rd rowArts Liaison
4th rowPrincipal
5th rowMusic Teacher
ValueCountFrequency (%)
principal 484
25.1%
assistant 247
12.8%
teacher 235
12.2%
arts 177
 
9.2%
art 135
 
7.0%
liaison 118
 
6.1%
visual 69
 
3.6%
music 43
 
2.2%
education 37
 
1.9%
ap 33
 
1.7%
Other values (141) 348
18.1%
2023-12-09T22:16:44.109982image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 1784
12.1%
a 1461
 
9.9%
s 1294
 
8.8%
r 1265
 
8.6%
n 1040
 
7.0%
t 1022
 
6.9%
946
 
6.4%
c 929
 
6.3%
e 708
 
4.8%
A 641
 
4.3%
Other values (46) 3692
25.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 11689
79.1%
Uppercase Letter 2030
 
13.7%
Space Separator 946
 
6.4%
Other Punctuation 108
 
0.7%
Dash Punctuation 5
 
< 0.1%
Decimal Number 4
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 1784
15.3%
a 1461
12.5%
s 1294
11.1%
r 1265
10.8%
n 1040
8.9%
t 1022
8.7%
c 929
7.9%
e 708
 
6.1%
l 624
 
5.3%
p 538
 
4.6%
Other values (13) 1024
8.8%
Uppercase Letter
ValueCountFrequency (%)
A 641
31.6%
P 540
26.6%
T 271
13.3%
L 162
 
8.0%
V 72
 
3.5%
E 67
 
3.3%
S 62
 
3.1%
M 59
 
2.9%
C 37
 
1.8%
D 30
 
1.5%
Other values (12) 89
 
4.4%
Other Punctuation
ValueCountFrequency (%)
/ 74
68.5%
. 12
 
11.1%
, 11
 
10.2%
& 8
 
7.4%
' 2
 
1.9%
; 1
 
0.9%
Decimal Number
ValueCountFrequency (%)
2 2
50.0%
5 1
25.0%
3 1
25.0%
Space Separator
ValueCountFrequency (%)
946
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 13719
92.8%
Common 1063
 
7.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 1784
13.0%
a 1461
10.6%
s 1294
9.4%
r 1265
9.2%
n 1040
 
7.6%
t 1022
 
7.4%
c 929
 
6.8%
e 708
 
5.2%
A 641
 
4.7%
l 624
 
4.5%
Other values (35) 2951
21.5%
Common
ValueCountFrequency (%)
946
89.0%
/ 74
 
7.0%
. 12
 
1.1%
, 11
 
1.0%
& 8
 
0.8%
- 5
 
0.5%
' 2
 
0.2%
2 2
 
0.2%
5 1
 
0.1%
; 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14782
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 1784
12.1%
a 1461
 
9.9%
s 1294
 
8.8%
r 1265
 
8.6%
n 1040
 
7.0%
t 1022
 
6.9%
946
 
6.4%
c 929
 
6.3%
e 708
 
4.8%
A 641
 
4.3%
Other values (46) 3692
25.0%

q44_3
Text

Distinct994
Distinct (%)99.8%
Missing4
Missing (%)0.4%
Memory size78.8 KiB
2023-12-09T22:16:44.442778image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length35
Median length32
Mean length23.71987952
Min length14

Characters and Unicode

Total characters23625
Distinct characters64
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique993 ?
Unique (%)99.7%

Sample

1st rowlsalmon@schools.nyc.gov
2nd rowjdugan6@schools.nyc.gov
3rd rowrfilippatos@schools.nyc.gov
4th rowbglover@schools.nyc.gov
5th rowJGouker@schools.nyc.gov
ValueCountFrequency (%)
jball3@schools.nyc.gov 3
 
0.3%
ediazwa@schools.nyc.gov 1
 
0.1%
jmayol@schools.nyc.gov 1
 
0.1%
aburnet2@schools.nyc.gov 1
 
0.1%
kalfano@schools.nyc.gov 1
 
0.1%
mgarfie@schools.nyc.gov 1
 
0.1%
ereingo@schools.nyc.gov 1
 
0.1%
cling2@schools.nyc.gov 1
 
0.1%
dmayo@schools.nyc.gov 1
 
0.1%
rbennett@erhsnyc.net 1
 
0.1%
Other values (984) 984
98.8%
2023-12-09T22:16:44.929450image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 3382
14.3%
s 2340
 
9.9%
c 2159
 
9.1%
. 1931
 
8.2%
n 1459
 
6.2%
l 1440
 
6.1%
g 1145
 
4.8%
h 1130
 
4.8%
y 1037
 
4.4%
v 996
 
4.2%
Other values (54) 6606
28.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 19649
83.2%
Other Punctuation 2927
 
12.4%
Uppercase Letter 577
 
2.4%
Decimal Number 471
 
2.0%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 3382
17.2%
s 2340
11.9%
c 2159
11.0%
n 1459
 
7.4%
l 1440
 
7.3%
g 1145
 
5.8%
h 1130
 
5.8%
y 1037
 
5.3%
v 996
 
5.1%
a 806
 
4.1%
Other values (16) 3755
19.1%
Uppercase Letter
ValueCountFrequency (%)
C 52
 
9.0%
S 51
 
8.8%
M 44
 
7.6%
L 43
 
7.5%
O 39
 
6.8%
A 33
 
5.7%
N 30
 
5.2%
J 28
 
4.9%
G 27
 
4.7%
K 26
 
4.5%
Other values (15) 204
35.4%
Decimal Number
ValueCountFrequency (%)
2 178
37.8%
3 80
17.0%
4 46
 
9.8%
1 44
 
9.3%
5 31
 
6.6%
6 25
 
5.3%
7 23
 
4.9%
9 17
 
3.6%
8 14
 
3.0%
0 13
 
2.8%
Other Punctuation
ValueCountFrequency (%)
. 1931
66.0%
@ 996
34.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 20226
85.6%
Common 3399
 
14.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 3382
16.7%
s 2340
11.6%
c 2159
10.7%
n 1459
 
7.2%
l 1440
 
7.1%
g 1145
 
5.7%
h 1130
 
5.6%
y 1037
 
5.1%
v 996
 
4.9%
a 806
 
4.0%
Other values (41) 4332
21.4%
Common
ValueCountFrequency (%)
. 1931
56.8%
@ 996
29.3%
2 178
 
5.2%
3 80
 
2.4%
4 46
 
1.4%
1 44
 
1.3%
5 31
 
0.9%
6 25
 
0.7%
7 23
 
0.7%
9 17
 
0.5%
Other values (3) 28
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 23625
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 3382
14.3%
s 2340
 
9.9%
c 2159
 
9.1%
. 1931
 
8.2%
n 1459
 
6.2%
l 1440
 
6.1%
g 1145
 
4.8%
h 1130
 
4.8%
y 1037
 
4.4%
v 996
 
4.2%
Other values (54) 6606
28.0%